Wafergraph MCP

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by jasonpalmer1 · TypeScript

Read-only MCP server for wafergraph.com's semiconductor & AI supply-chain data: 30 tools, no auth.

wafergraph-mcp (com.wafergraph/wafergraph-mcp)

Read-only MCP server that exposes wafergraph.com’s semiconductor & AI supply-chain dataset to MCP-speaking AI agents. It provides 30 tools over a streamable HTTP transport at /mcp, with a separate human landing page at /. No authentication is required and access is read-only.

🛠️ Key Features

Read-only MCP server for semiconductor & AI supply-chain data
30 tools exposed via streamable HTTP transport at /mcp
No auth, no cost
Dataset: 565 companies across 12 segments
Supplier/customer graph and a 74-deal M&A corpus
Tooling supports search_companies({query?, segment?, country?}) with segment and country filters, compact results capped at 25

🚀 Use Cases

Searching companies by name/description with segment and country filters
Querying relationships using the supplier/customer graph
Accessing a 74-deal M&A corpus for analysis

⚡ Developer Benefits

Direct callable tools for MCP-speaking agents
Streamable HTTP transport for integration
Filtered company search using query, segment, and country parameters

⚠️ Limitations

Read-only; no authentication is supported
Company search results are capped at 25 per call

Topics

cloudflare-workersmcpmcp-serversemiconductorssupply-chain

Captured live from the server via tools/list.

search_companies

Search wafergraph's semiconductor & AI supply-chain company dataset (615 companies across 12 segments) by name/one_liner substring and/or segment and/or country. Returns a compact list capped at 25 with a total match count. Use get_segments first if you don't know valid segment ids.

Parameters3

query	string	optional	Case-insensitive substring match against company name and one_liner.
segment	string	optional	Filter to companies with this taxonomy segment id, e.g. 'foundry', 'equipment_front_end' (see get_segments).
country	string	optional	Filter to companies headquartered in this country, e.g. 'Taiwan' (case-insensitive).

Raw schema

{
  "type": "object",
  "properties": {
    "query": {
      "description": "Case-insensitive substring match against company name and one_liner.",
      "type": "string"
    },
    "segment": {
      "description": "Filter to companies with this taxonomy segment id, e.g. 'foundry', 'equipment_front_end' (see get_segments).",
      "type": "string"
    },
    "country": {
      "description": "Filter to companies headquartered in this country, e.g. 'Taiwan' (case-insensitive).",
      "type": "string"
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_company

Full allowed profile for one company (by id or exact name) plus its supplier/customer supply-chain edges. Includes key_products (short list of named products/lines). Fields are deliberately limited to established/trust-checked data (see README field-discipline note).

Parameters1

string

required

Company id, snake_case (e.g. 'tsmc', 'asml') or exact company name.

Raw schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Company id, snake_case (e.g. 'tsmc', 'asml') or exact company name."
    }
  },
  "required": [
    "id"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_segments

The wafergraph taxonomy: 12 top-level supply-chain segments (materials through ai_datacenter) and their subsegments, each with a live company count, plus the market_position enum. Use this to discover valid `segment` values for search_companies/get_deals. Segment definitions are a versioned snapshot (see data.taxonomy_snapshot_date) while company counts are computed live.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_supply_chain

Walk the supplier/customer graph from one focal company, up to 2 tiers up (suppliers), down (customers), or both. Mirrors the chain view on wafergraph.com's Explorer. Returns companies grouped by tier plus the edges between them.

Parameters3

id	string	required	Focal company id or name.
direction	string	optional	up = walk suppliers only, down = walk customers only, both = walk both directions.
depth	integer	optional	Number of tiers to walk, capped at 2.

Raw schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Focal company id or name."
    },
    "direction": {
      "default": "both",
      "description": "up = walk suppliers only, down = walk customers only, both = walk both directions.",
      "type": "string",
      "enum": [
        "up",
        "down",
        "both"
      ]
    },
    "depth": {
      "default": 2,
      "description": "Number of tiers to walk, capped at 2.",
      "type": "integer",
      "minimum": 0,
      "maximum": 2
    }
  },
  "required": [
    "id"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_deals

Search wafergraph's semiconductor & AI supply-chain M&A corpus (74 acquisitions/mergers, including notable terminated attempts) by title/summary substring and/or segment. Returns a compact list capped at 30 with a total match count.

Parameters2

query	string	optional	Case-insensitive substring match against deal title and summary.
segment	string	optional	Filter to deals where at least one named party is a company in this taxonomy segment id.

Raw schema

{
  "type": "object",
  "properties": {
    "query": {
      "description": "Case-insensitive substring match against deal title and summary.",
      "type": "string"
    },
    "segment": {
      "description": "Filter to deals where at least one named party is a company in this taxonomy segment id.",
      "type": "string"
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

compare_companies

Side-by-side comparison of 2-6 companies on the same fields, plus their shared and unique supply-chain counterparties. Cheaper and more aligned than several get_company calls when the question is comparative.

Parameters1

ids

array

required

Company ids (snake_case, e.g. ['tsmc','samsung_foundry']) or exact names. 2-6 of them.

Raw schema

{
  "type": "object",
  "properties": {
    "ids": {
      "minItems": 2,
      "maxItems": 6,
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Company ids (snake_case, e.g. ['tsmc','samsung_foundry']) or exact names. 2-6 of them."
    }
  },
  "required": [
    "ids"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_country_exposure

Geographic concentration of the supply chain: which countries host the companies in a given segment (or across all 12 segments), ranked by company count. Answers 'how concentrated in Taiwan is advanced lithography' style questions. Country is recorded for all 615 companies.

Parameters1

segment

string

optional

Restrict to one taxonomy segment id (see get_segments). Omit for the whole dataset.

Raw schema

{
  "type": "object",
  "properties": {
    "segment": {
      "description": "Restrict to one taxonomy segment id (see get_segments). Omit for the whole dataset.",
      "type": "string"
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

find_chokepoints

Rank supply-chain chokepoints: companies many others depend on, weighted by how concentrated their market position is. A chokepoint here means high downstream dependency plus monopoly/leader position, i.e. few substitutes. Scoring is a transparent heuristic over the public dataset, not a proprietary risk model.

Parameters2

segment	string	optional	Restrict to one taxonomy segment id (see get_segments).
limit	integer	optional	How many to return (1-25, default 10).

Raw schema

{
  "type": "object",
  "properties": {
    "segment": {
      "description": "Restrict to one taxonomy segment id (see get_segments).",
      "type": "string"
    },
    "limit": {
      "default": 10,
      "description": "How many to return (1-25, default 10).",
      "type": "integer",
      "minimum": 1,
      "maximum": 25
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

analyze_portfolio_exposure

Given a list of tickers or company ids, report that basket's aggregate exposure across supply-chain segments and countries, and flag where holdings share the same upstream suppliers (correlated single points of failure). Informational supply-chain analysis over public data, not investment advice.

Parameters1

holdings

array

required

Tickers (e.g. ['NVDA','TSM']) or company ids. Up to 40.

Raw schema

{
  "type": "object",
  "properties": {
    "holdings": {
      "minItems": 1,
      "maxItems": 40,
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Tickers (e.g. ['NVDA','TSM']) or company ids. Up to 40."
    }
  },
  "required": [
    "holdings"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

filter_companies

Structured multi-criteria screen over all 615 companies: exact segment/subsegment/country/market_position/public filters plus a market-cap range, sortable and paginated. Use this instead of search_companies when the question is a precise filter ('leader-position analog companies in Japan under $20B') rather than a free-text match. Unknown segment/subsegment/country values just return zero results rather than erroring — call get_segments or list_subsegments first if you're not sure a value is valid.

Parameters11

segment	string	optional	Exact taxonomy segment id, e.g. 'foundry' (see get_segments).
subsegment	string	optional	Exact taxonomy subsegment id, e.g. 'litho' (see list_subsegments).
country	string	optional	Headquarters country, exact match, case-insensitive, e.g. 'Japan'.
market_position	string	optional	Exact market_position: monopoly \| leader \| major \| challenger \| niche.
public	boolean	optional	true = only publicly traded companies, false = only private ones. Omit for both.
min_market_cap_usd_b	number	optional	Minimum market cap in USD billions (inclusive). Only ~72% of companies have a cap on file — see the response note when this is set.
max_market_cap_usd_b	number	optional	Maximum market cap in USD billions (inclusive). Only ~72% of companies have a cap on file — see the response note when this is set.
has_ticker	boolean	optional	true = only companies with a public ticker on file, false = only companies without one.
sort_by	string	optional	Sort field. 'market_cap' sorts descending with unpriced companies last; 'name'/'country' sort ascending. Default 'market_cap'.
limit	integer	optional	Max rows to return, 1-100. Default 25.
offset	integer	optional	Rows to skip, for paging past the first `limit`. Default 0.

Raw schema

{
  "type": "object",
  "properties": {
    "segment": {
      "description": "Exact taxonomy segment id, e.g. 'foundry' (see get_segments).",
      "type": "string"
    },
    "subsegment": {
      "description": "Exact taxonomy subsegment id, e.g. 'litho' (see list_subsegments).",
      "type": "string"
    },
    "country": {
      "description": "Headquarters country, exact match, case-insensitive, e.g. 'Japan'.",
      "type": "string"
    },
    "market_position": {
      "description": "Exact market_position: monopoly | leader | major | challenger | niche.",
      "type": "string",
      "enum": [
        "monopoly",
        "leader",
        "major",
        "challenger",
        "niche"
      ]
    },
    "public": {
      "description": "true = only publicly traded companies, false = only private ones. Omit for both.",
      "type": "boolean"
    },
    "min_market_cap_usd_b": {
      "description": "Minimum market cap in USD billions (inclusive). Only ~72% of companies have a cap on file — see the response note when this is set.",
      "type": "number"
    },
    "max_market_cap_usd_b": {
      "description": "Maximum market cap in USD billions (inclusive). Only ~72% of companies have a cap on file — see the response note when this is set.",
      "type": "number"
    },
    "has_ticker": {
      "description": "true = only companies with a public ticker on file, false = only companies without one.",
      "type": "boolean"
    },
    "sort_by": {
      "default": "market_cap",
      "description": "Sort field. 'market_cap' sorts descending with unpriced companies last; 'name'/'country' sort ascending. Default 'market_cap'.",
      "type": "string",
      "enum": [
        "market_cap",
        "name",
        "country"
      ]
    },
    "limit": {
      "default": 25,
      "description": "Max rows to return, 1-100. Default 25.",
      "type": "integer",
      "minimum": 1,
      "maximum": 100
    },
    "offset": {
      "default": 0,
      "description": "Rows to skip, for paging past the first `limit`. Default 0.",
      "type": "integer",
      "minimum": 0,
      "maximum": 9007199254740991
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

list_subsegments

Every subsegment across wafergraph's 12-segment taxonomy, each with its live company count and parent segment id/name, optionally filtered to one segment. Use this (or get_segments) to discover valid `subsegment` values before calling get_subsegment or filter_companies. Segment/subsegment names come from a versioned taxonomy snapshot; company counts are computed live and can include subsegment ids present in the company data but not yet in that snapshot (flagged `in_taxonomy: false`).

Parameters1

segment

string

optional

Restrict to subsegments of this taxonomy segment id, e.g. 'materials'. Omit for all 12 segments.

Raw schema

{
  "type": "object",
  "properties": {
    "segment": {
      "description": "Restrict to subsegments of this taxonomy segment id, e.g. 'materials'. Omit for all 12 segments.",
      "type": "string"
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_subsegment

All companies in one segment+subsegment pair, as compact refs sorted by market cap descending, plus a market_position breakdown and a country breakdown computed over the FULL matching set (not just the returned page). Use list_subsegments first if you don't know valid segment/subsegment ids.

Parameters4

segment	string	required	Taxonomy segment id, e.g. 'equipment_front_end' (see get_segments).
subsegment	string	required	Taxonomy subsegment id within that segment, e.g. 'litho' (see list_subsegments).
limit	integer	optional	Max companies to return, 1-100. Default 50.
offset	integer	optional	Companies to skip, for paging past the first `limit`. Default 0.

Raw schema

{
  "type": "object",
  "properties": {
    "segment": {
      "type": "string",
      "description": "Taxonomy segment id, e.g. 'equipment_front_end' (see get_segments)."
    },
    "subsegment": {
      "type": "string",
      "description": "Taxonomy subsegment id within that segment, e.g. 'litho' (see list_subsegments)."
    },
    "limit": {
      "default": 50,
      "description": "Max companies to return, 1-100. Default 50.",
      "type": "integer",
      "minimum": 1,
      "maximum": 100
    },
    "offset": {
      "default": 0,
      "description": "Companies to skip, for paging past the first `limit`. Default 0.",
      "type": "integer",
      "minimum": 0,
      "maximum": 9007199254740991
    }
  },
  "required": [
    "segment",
    "subsegment"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

find_similar_companies

Nearest structural neighbours to one focal company, ranked by a transparent Jaccard-similarity score — not a market or competitive judgment. Use search_companies or resolve_ticker first if you only have a ticker or an approximate name, then pass the resolved id here.

Parameters2

id	string	required	Focal company id (snake_case, e.g. 'tsmc') or exact name to find neighbours for.
limit	integer	optional	How many similar companies to return, 1-25. Default 10.

Raw schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Focal company id (snake_case, e.g. 'tsmc') or exact name to find neighbours for."
    },
    "limit": {
      "default": 10,
      "description": "How many similar companies to return, 1-25. Default 10.",
      "type": "integer",
      "minimum": 1,
      "maximum": 25
    }
  },
  "required": [
    "id"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

rank_by_market_cap

Top N companies by market cap, optionally restricted to a segment/country/market_position, with the priced-coverage ratio for that scope attached — about 28% of companies dataset-wide have no market_cap_usd_b on file, so a plain top-N list without the coverage number would look more complete than it is.

Parameters4

limit	integer	optional	How many companies to return, ranked highest market cap first, 1-100. Default 10.
segment	string	optional	Restrict to one taxonomy segment id (see get_segments).
country	string	optional	Restrict to companies headquartered in this country, case-insensitive.
market_position	string	optional	Restrict to companies at this market_position.

Raw schema

{
  "type": "object",
  "properties": {
    "limit": {
      "default": 10,
      "description": "How many companies to return, ranked highest market cap first, 1-100. Default 10.",
      "type": "integer",
      "minimum": 1,
      "maximum": 100
    },
    "segment": {
      "description": "Restrict to one taxonomy segment id (see get_segments).",
      "type": "string"
    },
    "country": {
      "description": "Restrict to companies headquartered in this country, case-insensitive.",
      "type": "string"
    },
    "market_position": {
      "description": "Restrict to companies at this market_position.",
      "type": "string",
      "enum": [
        "monopoly",
        "leader",
        "major",
        "challenger",
        "niche"
      ]
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

resolve_ticker

Batch-resolve up to 25 strings — tickers, company names, or ids, in any mix — to canonical company refs. Call this FIRST whenever you have raw user input (a ticker list, pasted names) and need valid ids before calling other tools; unresolved entries come back with up to 3 suggested close matches instead of just null.

Parameters1

queries

array

required

Up to 25 strings to resolve, e.g. ['NVDA', 'TSMC', 'asml']. Each may be a ticker, an exact/partial company name, or a company id.

Raw schema

{
  "type": "object",
  "properties": {
    "queries": {
      "minItems": 1,
      "maxItems": 25,
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Up to 25 strings to resolve, e.g. ['NVDA', 'TSMC', 'asml']. Each may be a ticker, an exact/partial company name, or a company id."
    }
  },
  "required": [
    "queries"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

list_countries

Every country in wafergraph's semiconductor & AI supply-chain dataset (29 countries across 615 companies) with company count, which segments are present there (with counts), public/private split, and priced market-cap totals. Sorted by company count descending. Optional segment filter. country is the company's HEADQUARTERS country only, not a manufacturing-footprint field. A company headquartered here may fabricate, assemble, or test elsewhere — do not read this data as production geography.

Parameters1

segment

string

optional

Restrict to companies with this taxonomy segment id, e.g. 'foundry', 'memory' (see get_segments). Case-insensitive. Omit for all segments.

Raw schema

{
  "type": "object",
  "properties": {
    "segment": {
      "description": "Restrict to companies with this taxonomy segment id, e.g. 'foundry', 'memory' (see get_segments). Case-insensitive. Omit for all segments.",
      "type": "string"
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_country_profile

Deep profile of one country's presence in wafergraph's semiconductor & AI supply-chain dataset: company count, segment breakdown, market-position breakdown, top companies by market cap, notable monopoly/leader companies, and inbound/outbound supplier-relationship edge counts across this country's border (computed from the supply-chain graph). country is the company's HEADQUARTERS country only, not a manufacturing-footprint field. A company headquartered here may fabricate, assemble, or test elsewhere — do not read this data as production geography.

Parameters1

country

string

required

Country name, e.g. 'Taiwan', 'United States', 'South Korea'. Case-insensitive; common short forms (USA, UK, Korea) are recognized.

Raw schema

{
  "type": "object",
  "properties": {
    "country": {
      "type": "string",
      "description": "Country name, e.g. 'Taiwan', 'United States', 'South Korea'. Case-insensitive; common short forms (USA, UK, Korea) are recognized."
    }
  },
  "required": [
    "country"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

compare_countries

Side-by-side comparison of 2-5 countries: aligned rows for company count, segment mix, market-position mix, and priced market cap, plus which segments each country is uniquely present in or dominant in, and which segments they all share. country is the company's HEADQUARTERS country only, not a manufacturing-footprint field. A company headquartered here may fabricate, assemble, or test elsewhere — do not read this data as production geography.

Parameters1

countries

array

required

2-5 country names, e.g. ['Taiwan','South Korea','United States']. Case-insensitive; common short forms recognized.

Raw schema

{
  "type": "object",
  "properties": {
    "countries": {
      "minItems": 2,
      "maxItems": 5,
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "2-5 country names, e.g. ['Taiwan','South Korea','United States']. Case-insensitive; common short forms recognized."
    }
  },
  "required": [
    "countries"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_segment_leaders

Who runs a given layer of the semiconductor & AI supply chain: the companies at monopoly/leader market position in one taxonomy segment (or all 12 if none given), with country and market cap, plus a count of how many companies sit at each position (monopoly/leader/major/challenger/niche) in that segment. country is the company's HEADQUARTERS country only, not a manufacturing-footprint field. A company headquartered here may fabricate, assemble, or test elsewhere — do not read this data as production geography.

Parameters1

segment

string

optional

A taxonomy segment id, e.g. 'foundry', 'eda_ip' (see get_segments). Case-insensitive. Omit to cover all 12 segments.

Raw schema

{
  "type": "object",
  "properties": {
    "segment": {
      "description": "A taxonomy segment id, e.g. 'foundry', 'eda_ip' (see get_segments). Case-insensitive. Omit to cover all 12 segments.",
      "type": "string"
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_upstream_concentration

For one focal company: break its suppliers down by headquarters country and by segment, report an HHI concentration index (0 = spread evenly, 1 = fully concentrated in one bucket) for each dimension, and name the single most concentrated one. Always reports supplier_edge_coverage because key_suppliers is only ~58% filled dataset-wide — a company with few listed suppliers here may be under-documented, not genuinely un-dependent. country is the company's HEADQUARTERS country only, not a manufacturing-footprint field. A company headquartered here may fabricate, assemble, or test elsewhere — do not read this data as production geography.

Parameters1

string

required

Focal company id (snake_case, e.g. 'tsmc') or exact company name.

Raw schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Focal company id (snake_case, e.g. 'tsmc') or exact company name."
    }
  },
  "required": [
    "id"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

find_paths_between

Every documented supply path between two companies, following supplier->customer edges (e.g. 'how does NVIDIA actually depend on Shin-Etsu'). Searches up to max_depth hops in one or both directions and returns each path as an ordered list of companies, shortest first. Capped for combinatorial safety; absence of a path means undocumented, not disproven — see edge_coverage.

Parameters5

from	string	required	Starting company id, name, or ticker.
to	string	required	Target company id, name, or ticker.
max_depth	integer	optional	Maximum path length in hops (edges). Default 3, hard-capped at 4 to bound the search.
direction	string	optional	'downstream': paths where `from` supplies (directly or via intermediaries) to `to`. 'upstream': paths where `from` depends on `to` as a supplier. 'either': search both directions and label each path.
limit	integer	optional	Max number of paths to return (1-50, default 10).

Raw schema

{
  "type": "object",
  "properties": {
    "from": {
      "type": "string",
      "description": "Starting company id, name, or ticker."
    },
    "to": {
      "type": "string",
      "description": "Target company id, name, or ticker."
    },
    "max_depth": {
      "default": 3,
      "description": "Maximum path length in hops (edges). Default 3, hard-capped at 4 to bound the search.",
      "type": "integer",
      "minimum": 1,
      "maximum": 4
    },
    "direction": {
      "default": "either",
      "description": "'downstream': paths where `from` supplies (directly or via intermediaries) to `to`. 'upstream': paths where `from` depends on `to` as a supplier. 'either': search both directions and label each path.",
      "type": "string",
      "enum": [
        "upstream",
        "downstream",
        "either"
      ]
    },
    "limit": {
      "default": 10,
      "description": "Max number of paths to return (1-50, default 10).",
      "type": "integer",
      "minimum": 1,
      "maximum": 50
    }
  },
  "required": [
    "from",
    "to"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

simulate_disruption

Remove one company, every company in one country, or every company in one segment from the documented supply graph and report the blast radius: which companies lose a documented supplier, how many alternative suppliers they retain in the same subsegment, and which are left with zero documented alternative (ranked first). This is a documented-edge simulation, not a forecast — see the caveat field.

Parameters4

company_id	string	optional	Remove a single company by id, name, or ticker. Exactly one of company_id/country/segment is required.
country	string	optional	Remove every company headquartered in this country (case-insensitive exact match, e.g. 'Taiwan').
segment	string	optional	Remove every company in this taxonomy segment id (see get_segments).
limit	integer	optional	Max number of affected companies to return, zero-alternative ones first (1-100, default 20).

Raw schema

{
  "type": "object",
  "properties": {
    "company_id": {
      "description": "Remove a single company by id, name, or ticker. Exactly one of company_id/country/segment is required.",
      "type": "string"
    },
    "country": {
      "description": "Remove every company headquartered in this country (case-insensitive exact match, e.g. 'Taiwan').",
      "type": "string"
    },
    "segment": {
      "description": "Remove every company in this taxonomy segment id (see get_segments).",
      "type": "string"
    },
    "limit": {
      "default": 20,
      "description": "Max number of affected companies to return, zero-alternative ones first (1-100, default 20).",
      "type": "integer",
      "minimum": 1,
      "maximum": 100
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

find_single_source_dependencies

Screen for (customer, subsegment) pairs where the customer has exactly ONE documented supplier in that subsegment — the highest-value documented-concentration risk screen in the dataset. Optionally scoped to customers in one segment or country. Ranked by the sole supplier's downstream importance (its total documented customer count).

Parameters3

segment	string	optional	Restrict to customers in this taxonomy segment id (see get_segments). Omit for the whole dataset.
country	string	optional	Restrict to customers headquartered in this country (case-insensitive exact match).
limit	integer	optional	Max number of single-source pairs to return (1-100, default 25).

Raw schema

{
  "type": "object",
  "properties": {
    "segment": {
      "description": "Restrict to customers in this taxonomy segment id (see get_segments). Omit for the whole dataset.",
      "type": "string"
    },
    "country": {
      "description": "Restrict to customers headquartered in this country (case-insensitive exact match).",
      "type": "string"
    },
    "limit": {
      "default": 25,
      "description": "Max number of single-source pairs to return (1-100, default 25).",
      "type": "integer",
      "minimum": 1,
      "maximum": 100
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

rank_by_connectivity

Rank companies by documented supply-chain degree: customer count (downstream reach), supplier count (upstream dependence), or total. CRITICAL: degree measures how well a relationship is DOCUMENTED in this curated dataset, not how critical the company actually is — a well-covered firm can outrank a more essential but obscure one. See the caveat field in every response.

Parameters4

metric	string	optional	'customers' = downstream reach, 'suppliers' = upstream dependence, 'total' = sum of both.
segment	string	optional	Restrict to companies in this taxonomy segment id (see get_segments).
country	string	optional	Restrict to companies headquartered in this country (case-insensitive exact match).
limit	integer	optional	Max number of companies to return (1-50, default 15).

Raw schema

{
  "type": "object",
  "properties": {
    "metric": {
      "default": "total",
      "description": "'customers' = downstream reach, 'suppliers' = upstream dependence, 'total' = sum of both.",
      "type": "string",
      "enum": [
        "customers",
        "suppliers",
        "total"
      ]
    },
    "segment": {
      "description": "Restrict to companies in this taxonomy segment id (see get_segments).",
      "type": "string"
    },
    "country": {
      "description": "Restrict to companies headquartered in this country (case-insensitive exact match).",
      "type": "string"
    },
    "limit": {
      "default": 15,
      "description": "Max number of companies to return (1-50, default 15).",
      "type": "integer",
      "minimum": 1,
      "maximum": 50
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

find_common_suppliers

The shared-upstream question over a set of companies: given 2-15 company ids/tickers, or a segment id (uses every company in that segment), rank suppliers by how many of the input companies they documentedly serve (e.g. 'serves 9 of 12'), with each supplier's market position and country. Also reports how many input companies had no documented suppliers at all, since that makes a low overlap number ambiguous.

Parameters3

company_ids	array	optional	2-15 company ids, names, or tickers. Exactly one of company_ids/segment is required.
segment	string	optional	Use every company in this taxonomy segment id instead of an explicit list (see get_segments).
limit	integer	optional	Max number of ranked suppliers to return (1-100, default 20).

Raw schema

{
  "type": "object",
  "properties": {
    "company_ids": {
      "description": "2-15 company ids, names, or tickers. Exactly one of company_ids/segment is required.",
      "minItems": 2,
      "maxItems": 15,
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "segment": {
      "description": "Use every company in this taxonomy segment id instead of an explicit list (see get_segments).",
      "type": "string"
    },
    "limit": {
      "default": 20,
      "description": "Max number of ranked suppliers to return (1-100, default 20).",
      "type": "integer",
      "minimum": 1,
      "maximum": 100
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_deal

Full record for one M&A deal by id: title, type, value, announced date, status, all parties with their resolved company refs where a dataset id exists (and the raw party name where it does not), summary, sources, and the per-deal confidence flag. Use get_deals or find_deals_by_company to find a deal id first.

Parameters1

string

required

Deal id as returned by get_deals/find_deals_by_company, e.g. 'amd_xilinx_2020'.

Raw schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Deal id as returned by get_deals/find_deals_by_company, e.g. 'amd_xilinx_2020'."
    }
  },
  "required": [
    "id"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

find_deals_by_company

Every M&A deal a company took part in, split by role (as acquirer, as target, or other). Matches by dataset id first, then falls back to case-insensitive name matching — necessary because a deal's target is frequently not itself a company in this dataset and carries a null id (e.g. AMD's acquisition of Xilinx lists acquirer id 'amd' but target id null, name 'Xilinx'). Each matched deal carries a match_method ('id' or 'name') so weaker name-only matches are visible to the caller.

Parameters1

company

string

required

Company id, exact name, or ticker to search for across all deal parties, e.g. 'amd', 'Xilinx', 'AMD'.

Raw schema

{
  "type": "object",
  "properties": {
    "company": {
      "type": "string",
      "description": "Company id, exact name, or ticker to search for across all deal parties, e.g. 'amd', 'Xilinx', 'AMD'."
    }
  },
  "required": [
    "company"
  ],
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_ma_activity_summary

Aggregate view of the full 74-deal M&A corpus: counts by year (from announced date), by deal type, and by status; total and median disclosed value; and the largest deals by value. Value figures are computed only over the subset of deals with a disclosed value_usd and are never extrapolated to cover the undisclosed ones.

Parameters1

top_n

integer

optional

How many largest-by-value deals to return, 1-25 (default 10).

Raw schema

{
  "type": "object",
  "properties": {
    "top_n": {
      "default": 10,
      "description": "How many largest-by-value deals to return, 1-25 (default 10).",
      "type": "integer",
      "minimum": 1,
      "maximum": 25
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

find_consolidation_hotspots

Ranks taxonomy segments by M&A activity by mapping each deal's parties onto their companies' segments (matching by id, then falling back to case-insensitive name), then aggregating deal count and disclosed value per segment. Deals whose parties cannot be resolved to any dataset company are counted in unmapped_deals rather than dropped, so thinly-covered segments aren't silently underrepresented.

Parameters2

limit	integer	optional	How many ranked segments to return, 1-12 (there are 12 segments total).
sort_by	string	optional	Rank segments by number of deals ('deal_count') or by summed disclosed deal value ('value').

Raw schema

{
  "type": "object",
  "properties": {
    "limit": {
      "default": 12,
      "description": "How many ranked segments to return, 1-12 (there are 12 segments total).",
      "type": "integer",
      "minimum": 1,
      "maximum": 12
    },
    "sort_by": {
      "default": "deal_count",
      "description": "Rank segments by number of deals ('deal_count') or by summed disclosed deal value ('value').",
      "type": "string",
      "enum": [
        "deal_count",
        "value"
      ]
    }
  },
  "$schema": "http://json-schema.org/draft-07/schema#"
}

get_dataset_stats

The honesty tool: what this dataset actually contains and where it is thin. Live-computed per-field coverage for companies and deals, last_verified staleness distribution, supply-chain edge coverage, data source mode, and a plain-words list of known limitations. Call this before treating an absence of a company, deal, or edge as evidence it doesn't exist in the real market.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "$schema": "http://json-schema.org/draft-07/schema#"
}

README.md7 KBView on GitHub

wafergraph-mcp

A remote MCP server exposing wafergraph.com's semiconductor & AI supply-chain dataset — 565 companies across 12 segments, the supplier/customer graph, and a 74-deal M&A corpus — as 30 read-only tools any MCP-speaking AI agent can call directly.

No auth, no cost, read-only. Streamable HTTP transport at /mcp. Human landing page at /.

Live: https://mcp.wafergraph.com

Tools

Tool	Purpose
`search_companies({query?, segment?, country?})`	Name/description search with segment & country filters. Compact list, capped at 25, with a total match count.
`get_company({id})`	Full allowed profile for one company (by id or name) plus its supplier/customer edges.
`get_segments()`	The 12-segment taxonomy (+ subsegments, market_position enum) with live company counts.
`get_supply_chain({id, direction, depth})`	Walk the supplier/customer graph from a focal company up to 2 tiers up (`"up"`), down (`"down"`), or `"both"`.
`get_deals({query?, segment?})`	Search the M&A deal corpus. Compact list, capped at 30, with a total match count.
`compare_companies({ids})`	Side-by-side comparison of 2-6 companies on aligned fields, plus their shared and unique supply-chain counterparties.
`get_country_exposure({segment?})`	Geographic concentration: which countries host a segment's companies, ranked by count, with disclosed market-cap coverage.
`find_chokepoints({segment?, limit?})`	Rank chokepoints by downstream dependency weighted by market position. Transparent heuristic, not a proprietary risk model.
`analyze_portfolio_exposure({holdings})`	Map tickers or ids to segment/country exposure and flag suppliers that several holdings share. Not investment advice.

Screening & discovery

Tool	Purpose
`filter_companies({...})`	Structured multi-criteria screen (segment, subsegment, country, position, public, market-cap band, has_ticker) with sorting and pagination.
`list_subsegments({segment?})`	Every subsegment with its live company count and parent segment.
`get_subsegment({segment, subsegment})`	All companies in one subsegment with position and country breakdowns.
`find_similar_companies({id})`	Nearest structural neighbours by Jaccard similarity over segment tags and shared supply-chain counterparties.
`rank_by_market_cap({segment?, country?, limit?})`	Largest companies by disclosed market cap, always with its coverage ratio.
`resolve_ticker({inputs})`	Batch-resolve up to 25 tickers, names, or ids to canonical companies, with suggestions on a miss.

Geography & structure

Tool	Purpose
`list_countries({segment?})`	Every country with company counts, segment mix, and public/private split.
`get_country_profile({country})`	One country in depth, including how many supply relationships cross its border in each direction.
`compare_countries({countries})`	2-5 countries side by side, with uniquely-present and dominant segments.
`get_segment_leaders({segment?})`	Who occupies the monopoly and leader positions in a segment.
`get_upstream_concentration({id})`	One company's supplier mix by country and segment with an HHI index and edge-coverage context.

Graph analysis

Tool	Purpose
`find_paths_between({from, to, max_depth?})`	Documented supply paths between two companies, shortest first.
`simulate_disruption({company_id?	country?
`find_single_source_dependencies({segment?, country?})`	Customer/subsegment pairs served by exactly one documented supplier.
`rank_by_connectivity({metric?, limit?})`	Rank by documented degree. Measures documentation density, not real-world criticality.
`find_common_suppliers({ids?	segment?})`

Deals & dataset

Tool	Purpose
`get_deal({id})`	One M&A deal in full, with parties resolved to companies where possible.
`find_deals_by_company({id})`	Every deal a company took part in, split by role, with the match method exposed.
`get_ma_activity_summary()`	Deal counts and disclosed values by year, type, and status.
`find_consolidation_hotspots()`	Which segments are consolidating, with unresolvable deals counted rather than dropped.
`get_dataset_stats()`	What this dataset contains, how fresh it is, and where it is thin. Call it to learn what the data cannot answer.

Every response includes:

data — the payload.
attribution — compiled-by/sources block (SEC, Wikidata, Wikipedia, GLEIF) plus a company_url back to the full sourced profile on wafergraph.com.
links — { report, newsletter } pointing back to wafergraph.com and its hand-scored Vendor Exposure Review.

Field discipline

Company records include key_products as of 2026-07-19. That field in wafergraph's own dataset was originally bulk-drafted with a known fabrication/mis-scope history and was withheld here until a verified deep-fill landed upstream; it now has (confirmed live) 564/565 companies filled, with only sk_enpulse empty (defunct, absorbed into SKC 2025-12-23). Every field shipped here — name, ticker, market_cap_usd_b, segments, one_liner, market_position, key_products, key_customers/key_suppliers graph edges, deals — is established, trust-checked data. Fields are still whitelisted (not blacklisted) in src/types.ts (toAllowedCompany), so anything added upstream later stays excluded by default until deliberately added.

What this server records

Counters only, never identities. No IPs, no query contents or tool arguments, no user identifiers, no cookies, no PII. Specifically: how many times each tool was called per day, how many distinct sessions opened per day, and which client software connected (the clientInfo name and version your MCP client already sends in the initialize handshake, e.g. claude-code@2.1.0).

Sessions are not users — one person reconnecting counts several times. Nothing recorded here can identify who you are.

Install

Claude Code

code

claude mcp add --transport http wafergraph https://mcp.wafergraph.com/mcp

claude.ai (custom connector)

Settings → Connectors → Add custom connector → paste:

code

https://mcp.wafergraph.com/mcp

Generic MCP client (Streamable HTTP)

json

{
  "mcpServers": {
    "wafergraph": {
      "url": "https://mcp.wafergraph.com/mcp"
    }
  }
}

Architecture

Cloudflare Worker, TypeScript, built on the agents package's McpAgent (Durable-Object-backed Streamable HTTP MCP server — free on the Workers Free plan; SQLite storage backend). See CLAUDE.md for the file map and the data-source-mode decision (hybrid live-fetch + one vendored snapshot, discovered by E2E-testing the upstream endpoints rather than assumed).

Development

bash

npm install
npm run dev       # wrangler dev, local
npm run typecheck # tsc --noEmit
npm run deploy    # wrangler deploy

Attribution & licensing

See ATTRIBUTION.md for the full source/license breakdown (SEC EDGAR public domain, Wikidata CC0, Wikipedia CC BY-SA 4.0 — attribution required, GLEIF). Short version: free to use, credit wafergraph.com, not financial advice.

This is an independent project built against wafergraph.com's public dataset; it is not an official wafergraph product.

Install

Tools (30)

search_companiesget_companyget_segmentsget_supply_chainget_dealscompare_companiesget_country_exposurefind_chokepoints

Remote endpoint

Streamable HTTP

Hosted server - connect over the network, no local install.

url

https://wafergraph-mcp.jwpalm99.workers.dev/mcp

Add to VS Code Add to Cursor

claude_desktop_config.json

json

{
  "mcpServers": {
    "wafergraph-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://wafergraph-mcp.jwpalm99.workers.dev/mcp"
      ]
    }
  }
}

Desktop config is stdio-only; this bridges via mcp-remote. Native remote: Settings > Connectors.

wafergraph-mcp (com.wafergraph/wafergraph-mcp)

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

Topics

search_companies

get_company

get_segments

get_supply_chain

get_deals

compare_companies

get_country_exposure

find_chokepoints

analyze_portfolio_exposure

filter_companies

list_subsegments

get_subsegment

find_similar_companies

rank_by_market_cap

resolve_ticker

list_countries

get_country_profile

compare_countries

get_segment_leaders

get_upstream_concentration

find_paths_between

simulate_disruption

find_single_source_dependencies

rank_by_connectivity

find_common_suppliers

get_deal

find_deals_by_company

get_ma_activity_summary

find_consolidation_hotspots

get_dataset_stats

wafergraph-mcp

Tools

Screening & discovery

Geography & structure

Graph analysis

Deals & dataset

Field discipline

What this server records

Install

Claude Code

claude.ai (custom connector)

Generic MCP client (Streamable HTTP)

Architecture

Development

Attribution & licensing

Install

Remote endpoint

Related servers