WHO GHO MCP Server

WHO GHO MCP (io.github.pipeworx-io/who-gho) exposes World Health Organization Global Health Observatory data through the Model Context Protocol. It provides access to ~3,000 health-related indicators across 194 member states spanning mortality, disease prevalence, healthcare workforce, immunization, environmental health, NCDs, communicable diseases, and demographics. It is free and requires no authentication.

🛠️ Key Features

MCP server for WHO GHO data access
~3,000 indicators across 194 member states
Coverage includes mortality, prevalence, workforce, immunization, environmental health, NCDs, communicable diseases, and demographics
34 tools available
Topics: mcp, mcp-server, model-context-protocol, pipeworx, who-gho

🚀 Use Cases

International comparisons of health indicators
Country-level public-health snapshots from a canonical international health-data source

⚡ Developer Benefits

No-auth access suitable for automated data retrieval
Standardized Model Context Protocol interface (as an MCP server)

⚠️ Limitations

Described scope is the WHO GHO database; other sources are not indicated

WHO GHO — World Health Organization Global Health Observatory

The World Health Organization's GHO database. ~3,000 health-related indicators across 194 member states: mortality, disease prevalence, healthcare workforce, immunization, environmental health, NCDs, communicable diseases, demographics. The canonical international health-data source. Free, no auth.

Part of Pipeworx — an MCP gateway connecting AI agents to 1476+ live data sources.

Why this matters for AI agents

For international comparisons of health indicators or country-level public-health snapshots, WHO GHO is the source. Where CDC is US-focused, WHO is global. Pair with World Bank (development indicators) and IMF (macro) for full country-level analysis.

Common flows:

Country indicator. "Life expectancy in Brazil?" → indicator + country query.
Cross-country comparison. Same indicator across multiple countries.
Time series. Indicator over years for trend analysis.
Indicator browse. "What does WHO publish on diabetes?" → search the indicator catalog.

Auth

None. WHO GHO is fully public, free.

Indicator categories

Major categories (each with dozens to hundreds of indicators):

Mortality and life expectancy
Communicable diseases (HIV, TB, malaria, COVID-19, vaccine-preventable)
Non-communicable diseases (cardiovascular, cancer, diabetes, mental health)
Maternal and child health
Health workforce (physicians, nurses, beds per 1000)
Environmental health (air pollution, water/sanitation access)
Health systems financing
Risk factors (tobacco, alcohol, BMI, blood pressure)

Common pitfalls

Country reporting quality varies. Wealthy countries report comprehensively; lower-income countries have data gaps and longer lags. Some indicators are WHO-modeled estimates filling country reporting gaps.
Disaggregation availability. "Indicator X for country Y" may not break down by sex, age, or urban/rural. Check whether the disaggregation you want exists before building queries that depend on it.
Definition shifts. WHO occasionally revises indicator methodology (e.g., changing definition of "stunting" cut-points). Long time series across methodology changes need annotation.
Lag. Most WHO data lags 1-3 years. Recent year may have only modeled estimates. For real-time outbreak data, use WHO's separate disease-surveillance feeds.
Country naming. WHO uses ISO 3-letter codes. Some politically-disputed entities (Taiwan, Palestine, Kosovo) have inconsistent treatment in headline data; check coverage explicitly.
Population denominator. Per-capita rates are usually computed against UN population estimates. Different sources (UN vs. national stats) can differ slightly, especially for fast-growing populations.
WHO regions. WHO groups countries into 6 regions (Africa, Americas, Eastern Mediterranean, Europe, Southeast Asia, Western Pacific). These don't match World Bank or other regional groupings.

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

json

{
  "mcpServers": {
    "who-gho": {
      "url": "https://gateway.pipeworx.io/who-gho/mcp"
    }
  }
}

What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/who-gho/mcp returns the tools in the table above plus the shared Pipeworx meta-tools — ask_pipeworx, discover_tools, search_within, remember/recall and the rest of the gateway-wide set. So the tool count you see is larger than this table: a single-pack endpoint currently lists roughly 30 shared tools alongside the pack's own. The connection's initialize response states its exact scope, and is the authoritative answer for a given day.

This is deliberate, not multiplexing by accident. The meta-tools are what let a scoped connection answer a question this pack does not cover — via ask_pipeworx, which routes across the whole catalog — without you adding a second MCP server. There is currently no way to mount a pack endpoint without them; if the extra schemas cost you more context than the routing is worth, connect to the full gateway once rather than to several pack endpoints.

Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:

json

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://gateway.pipeworx.io/mcp"
    }
  }
}

Both URLs reach the same gateway and the same 1476+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

Using with ask_pipeworx

Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:

code

ask_pipeworx({ question: "your question about Who Gho data" })

The gateway picks the right tool and fills the arguments automatically.

License

MIT

question	string	required	Your question or request in natural language. Accepts query, q, prompt, text, input as aliases.
query	string	optional	Alias for question.
q	string	optional	Alias for question.
prompt	string	optional	Alias for question.
text	string	optional	Alias for question.
input	string	optional	Alias for question.

question	string	required	Your question or request in natural language. Accepts query, q, prompt, text, input as aliases.
query	string	optional	Alias for question.
q	string	optional	Alias for question.
prompt	string	optional	Alias for question.
text	string	optional	Alias for question.
input	string	optional	Alias for question.

question	string	required	Your question in natural language. Accepts query, q, prompt, text, input as aliases.
query	string	optional	Alias for question.
q	string	optional	Alias for question.
prompt	string	optional	Alias for question.
text	string	optional	Alias for question.
input	string	optional	Alias for question.

text	string	required	The document text to search inside (max ~200K chars).
query	string	required	Natural-language query — what passages do you want? E.g. "supply-chain risk", "fiscal year 2024 revenue", "drug interactions with warfarin".
limit	number	optional	Max passages to return (1-20, default 5).

question	string	required	The research question, in natural language. Broad/multi-part is fine — decomposition is the point.
depth	string	optional	How many facets to research in parallel: quick=3 (single hop), standard=5 (default; adds a gap-recovery hop that re-angles unanswered facets + a contradictions[] scan across findings), thorough=8 (paid; adds a full iterative hop that chases leads + recovers gaps, plus the contradictions[] scan).

type	string	required	Entity type: "company" or "drug".
value	string	required	For company: ticker (AAPL), CIK (0000320193), or name. For drug: brand or generic name (e.g., "ozempic", "metformin").

claim	string	required	Natural-language factual claim, e.g., "Apple's FY2024 revenue was $400 billion" or "Microsoft made about $100B in profit last year".
tolerance_pct	number	optional	Max percent deviation still graded approximately_correct (0.5–50). Overrides the tolerance implied by the claim wording — set 1–2 for hallucination detection where any material error must be refuted. Default: implied by wording, capped at 5.

package	string	required	npm package name. Scoped packages (e.g. "@types/node") are accepted.
version	string	optional	Specific version to check (e.g., "18.3.1"). Defaults to the latest published version when omitted.

market	string	required	Polymarket slug ("will-bitcoin-hit-150k-by-june-30-2026"), full URL ("https://polymarket.com/event/..."), or question text ("Will Bitcoin hit $150k by June 30?")
depth	string	optional	quick = 2-3 evidence sources, thorough = full fan-out. Default thorough.
include_raw	boolean	optional	Default false. When false (recommended), FRED/FDA/GDELT/Federal-Register evidence is summarized to the few fields agents actually use — keeps responses under ~20KB. Pass true to get full upstream payloads (50KB-500KB) when you need to recompute deltas, cite specific observations, or post-process.

event	string	optional	Single-event mode (use this if you know the specific Polymarket event): event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k". Full Polymarket URLs also accepted.
topic	string	optional	Cross-event mode (use this if you want to scan related events across the platform): a topic or seed question like "Fed rate decision" or "Strait of Hormuz traffic returns to normal". Tool searches Polymarket for related events and checks monotonicity across them.

window	string	optional	Polymarket volume window to filter markets. Default 1wk.
limit	number	optional	Top N edges to return after ranking. Default 10, max 25.
min_edge_pp	number	optional	Minimum \|edge\| in percentage points to include (default 0.5). Edge is evaluated NET of slippage.
slippage_pp	number	optional	Assumed execution slippage in percentage points per leg (default 0.3). Subtracted from raw \|edge\| before ranking and Kelly sizing. Polymarket has zero trading fees as of 2024 but bid/ask + thin depth typically eats 20-50bp per trade. Bump for very thin partitions; drop to 0 if you have a smarter fill model.
category_filter	string	optional	Comma-separated list to restrict the output: "model_driven" (crypto_price + news_momentum), "structural_arbitrage" (partition_overround), "concentrated_longshot". Combine like "model_driven,structural_arbitrage". Default: all.
min_kelly	number	optional	Minimum half-Kelly fraction (as decimal, e.g. 0.005 = 0.5% of bankroll) to include single-leg opportunities. Default 0 (no filter). Skips opportunities that are too small to bet sensibly even if the edge is large.
min_partition_leg_kelly	number	optional	Minimum BEST per-leg half-Kelly fraction across a partition_overround opportunity's top_legs (or longshot_basket legs). Default 0 (no filter). Partition arbs always return kelly_fraction_half=0 at the parent level by design (basket trades don't compose to single-leg Kelly), so min_kelly never filters them — this knob applies to the per-leg Kelly inside top_legs instead. Use to suppress thin partitions whose individual leg edges aren't worth the per-leg slippage cost.
min_liquidity	number	optional	Tradeable-edge filter. Minimum $ liquidity on the representative market (or for partition_overround, on at least one top_leg). Default 0 (no filter). Set to 5000 to drop thin-book opportunities where executing the edge would walk the book past breakeven.
max_spread_pp	number	optional	Tradeable-edge filter. Maximum bid/ask spread in percentage points on the representative market. Default null (no filter). Set to 2 to require tight books — anything wider eats most plausible edges.

days	number	optional	Lookback in days (default 14, clamp 2-30).
window	string	optional	Which polymarket_edges window family to read snapshots for: 24hr \| 1wk \| 1mo (default 1wk).

url	string	required	Full URL of the site to summarize, e.g. "https://example.com" or a specific landing page.
max_links	number	optional	Maximum number of link entries to include (default 25, max 50).

entity	string	required	The thing to ask about. Brand/business name, product name, person, or topic. E.g. "Pipeworx", "OpenInvoice", "Acme Corp pricing".
context	string	optional	Optional: a phrase locating the entity (e.g. "Boston restaurant", "B2B SaaS"). Helps disambiguate common names.
models	array	optional	Which models to probe. Supported: "workers-ai" (free default), "anthropic" (requires _apiKey). Omit for just workers-ai.
_apiKey	string	optional	Optional Anthropic API key (sk-ant-...) — only needed if "anthropic" is in models. Passed straight through to api.anthropic.com.

entities	array	required	Array of 2-8 entities to compare (brand/business/product names). First entry treated as the "subject" for narrative; rest are competitors.
context	string	optional	Optional shared context applied to every probe (e.g. "B2B SaaS", "Boston restaurant"). Disambiguates common names.
models	array	optional	Which models to probe. Supported: "workers-ai" (free default), "anthropic" (requires _apiKey). Omit for just workers-ai.
_apiKey	string	optional	Optional Anthropic API key — only if "anthropic" is in models. Passed to api.anthropic.com per probe.

type	string	required	Subscription type.
params	object	required	Type-specific filter. sec_8k: {ticker:"AAPL", items?:["5.02","1.01"]}. polymarket_edge: {topic:"fed", min_spread_bps?:500}. fred_series: {series_id:"UNRATE"}. patent_grant: {applicant:"Apple Inc."}. clinical_trial: {sponsor?:"Pfizer", condition?:"lung cancer", phase?:"PHASE3"} (sponsor or condition required).
delivery	object	optional	Optional delivery channels in addition to the always-on persistent feed. {email:"you@x.com"} sends a templated alert per fired event. {sms:"+15551234567"} sends an SMS per event — must match the verified phone on the caller's account (verify at https://pipeworx.io/account first; 10/day cap). {webhook:"https://..."} POSTs each event JSON to your endpoint, HMAC-signed — the response includes delivery.webhook_secret (whsec_…) ONCE; verify X-Pipeworx-Signature = sha256 HMAC of "<X-Pipeworx-Timestamp>.<raw body>". Auto-disabled after 10 consecutive failing runs.

type	string	required	Entity type. Only "company" supported today.
value	string	required	Ticker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").
since	string	required	Window start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.

topic	string	optional	Pre-mapped: fed \| btc \| cpi \| gdp \| sp500 \| recession \| next_pope \| next_uk_pm \| next_israel_pm \| 2028_president
kalshi_event_ticker	string	optional	Explicit Kalshi event ticker, e.g. "KXFED-26OCT". Overrides the topic-mapped Kalshi side.
polymarket_event_slug	string	optional	Explicit Polymarket event slug, e.g. "fed-decision-in-june-825". Overrides the topic-mapped Polymarket side.

market	string	optional	Single-market mode: market slug or full polymarket.com URL.
event	string	optional	Basket mode: event slug or full polymarket.com URL — checks every leg of the partition.
side	string	optional	Single-market: buy_yes \| sell_yes \| buy_no \| sell_no (default buy_yes). Basket: sell_yes \| buy_yes (default auto — sell if partition sum > 1, buy if < 1).
size_usd	number	optional	Single-market: USD to spend (buys) or target proceeds (sells). Basket: settlement notional — shares per leg, each paying $1 at resolution. Default 1000, clamp 10–1,000,000.

key	string	required	Memory key (e.g., "subject_property", "target_ticker", "user_preference")
value	string	required	Value to store (any text — findings, addresses, preferences, notes)

indicator	string	required	WHO indicator code (e.g., "WHOSIS_000001" for life expectancy)
country	string	optional	ISO 3-letter country code (e.g., "USA", "GBR", "JPN")
year	string	optional	Year to filter by (e.g., "2020")

WHO GHO MCP Server

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

Topics

ask_pipeworx

ask_pipeworx_beta

ask_pipeworx_grounded

search_within

deep_research

discover_tools

resolve_entity

compare_entities

subscribe

unsubscribe

list_subscriptions

recent_alerts

entity_profile

recent_changes

validate_claim

scan_dependency

bet_research

polymarket_arbitrage

polymarket_edges

polymarket_kalshi_spread

polymarket_fill_risk

polymarket_edge_tracker

pipeworx_trending

suggest_questions

generate_llms_txt

ai_visibility_check

scan_competitor_ai_presence

pipeworx_feedback

remember

recall

forget

get_indicators

get_data

list_countries

WHO GHO — World Health Organization Global Health Observatory

Why this matters for AI agents

Auth

Indicator categories

Common pitfalls

Quick Start

What this endpoint actually serves

Using with ask_pipeworx

More

License

Install

Remote endpoint

Related servers