LiquiLens — the Failure Radar

Official23 toolsLive

by beepboop2025 · Python

Free bank-filing and counterparty research; cited evidence limits; public MCP needs no API key.

LiquiLens MCP — the Failure Radar as agent tools

LiquiLens provides a free bank research workflow for early failure detection, focusing on NPA reconciliation, small finance banks, UCBs, and cited evidence limits. This MCP server exposes the same validation record alongside each claim so LLM agents can read the record using a streamable HTTP endpoint.

🛠️ Key Features

NPA reconciliation research
Coverage for small finance banks and UCBs
Validation record served beside every claim
Endpoint available at https://api.liquilens.in/mcp (streamable HTTP, no auth, no install)
Tool set count: 18

🚀 Use Cases

Bank/lender research using public data
Reviewing cited evidence limits with each claim
Performing NPA reconciliation analysis via agent tools

⚡ Developer Benefits

Shared record format between agents and humans
Direct MCP access over HTTP at the published endpoint
Tool-based retrieval for bank research tasks

⚠️ Limitations

Described as “failure early-warning system” based on the provided public data and the cited evidence limits it enforces.

Topics

ai-agentsbankingearly-warningfinancial-riskmcp-serverliquidity-riskmodel-context-protocolopen-datafintechmcpnbfcrbiautomationhermes-agentopenclaw

Captured live from the server via tools/list.

bank_asset_quality_review

Sourced GNPA/NNPA, percentage-point changes, PCR definitions, capital scope and NPA reconciliation with SFB/UCB context. Free; no score, credit or execution authority.

Parameters3

slug	string	required
as_of	string	optional	End-of-day YYYY-MM-DD cutoff; not future.
include_history	boolean	optional

Raw schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string"
    },
    "as_of": {
      "type": "string",
      "format": "date",
      "description": "End-of-day YYYY-MM-DD cutoff; not future."
    },
    "include_history": {
      "type": "boolean",
      "default": false
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false
}

bank_npa_reconciliation

Check supplied NPA stock movements. Keep recoveries, write-offs, sales and upgrades distinct. Free arithmetic; no input authentication or loan classification.

Parameters1

statement

object

required

Raw schema

{
  "type": "object",
  "properties": {
    "statement": {
      "type": "object",
      "properties": {
        "period_start": {
          "type": "string",
          "format": "date"
        },
        "period_end": {
          "type": "string",
          "format": "date"
        },
        "amount_unit": {
          "type": "string",
          "enum": [
            "INR_crore",
            "INR_lakh",
            "INR",
            "INR_thousand"
          ]
        },
        "opening_gnpa": {
          "type": "number",
          "minimum": 0,
          "maximum": 1000000000000000000
        },
        "additions": {
          "type": "number",
          "minimum": 0,
          "maximum": 1000000000000000000
        },
        "closing_gnpa": {
          "type": "number",
          "minimum": 0,
          "maximum": 1000000000000000000
        },
        "rounding_decimals": {
          "type": "integer",
          "minimum": 0,
          "maximum": 6
        },
        "complete": {
          "type": "boolean"
        },
        "reductions": {
          "type": "array",
          "maxItems": 16,
          "items": {
            "type": "object",
            "properties": {
              "kind": {
                "type": "string",
                "enum": [
                  "cash_recoveries",
                  "upgrades",
                  "write_offs",
                  "asset_sales",
                  "compromise_settlements",
                  "combined_reductions",
                  "other_reductions"
                ]
              },
              "amount": {
                "type": "number",
                "minimum": 0,
                "maximum": 1000000000000000000
              }
            },
            "required": [
              "kind",
              "amount"
            ],
            "additionalProperties": false
          }
        }
      },
      "required": [
        "period_start",
        "period_end",
        "amount_unit",
        "opening_gnpa",
        "additions",
        "closing_gnpa",
        "reductions",
        "complete",
        "rounding_decimals"
      ],
      "additionalProperties": false
    }
  },
  "required": [
    "statement"
  ],
  "additionalProperties": false
}

banking_specialisation_coverage

Indian bank, SFB and UCB coverage with observed, stale, historical and absent evidence. Free research; not a census or rating.

Parameters2

sector	string	optional
as_of	string	optional	End-of-day YYYY-MM-DD cutoff; not future.

Raw schema

{
  "type": "object",
  "properties": {
    "sector": {
      "type": "string",
      "enum": [
        "all",
        "bank",
        "sfb",
        "ucb"
      ]
    },
    "as_of": {
      "type": "string",
      "format": "date",
      "description": "End-of-day YYYY-MM-DD cutoff; not future."
    }
  },
  "additionalProperties": false
}

corporate_transmission_board

Answers ONE question: is US funding stress reaching nonfinancial firms? Use household_credit_board for households. CP, bank credit lines and real-economy confirmation; cannot_see preserves gaps. Seiche context never enters regime or transmission. Display-only; no institution score or tier. full:true adds methods.

Parameters1

full

boolean

optional

also return method_note, thresholds and per-leg basis prose (larger payload); default false

Raw schema

{
  "type": "object",
  "properties": {
    "full": {
      "type": "boolean",
      "description": "also return method_note, thresholds and per-leg basis prose (larger payload); default false",
      "default": false
    }
  },
  "additionalProperties": false
}

crypto_exposure_board

Read the compact cited bank/crypto exposure register: disclosed quantum, stablecoin and venue links, exposure channels, Undertow run-risk cross-read and compound flags. Detailed disclosures stay on the public REST detail route. Takes no arguments; display-only, never an institution score or investment advice.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

crypto_regime_board

Read the compact BTC/ETH Crypto Regime board: current change-point state, log-SR statistic, last shift, observation count and the display-only cross-read against disclosed bank exposure. Time-series paths stay on the public REST detail route. Takes no arguments; feeds no institution score and is not investment advice.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

evidence_europe

Read seven cited European retrospective case files through unrecalibrated Indian lenses. Named case studies, not a cohort: no European recall percentage to quote. Omit slug for summaries, or supply a returned slug for a full quarterly case file.

Parameters1

slug

string

optional

optional kebab-case case-file slug, e.g. 'credit-suisse'; omit for all seven summaries

Raw schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "optional kebab-case case-file slug, e.g. 'credit-suisse'; omit for all seven summaries"
    }
  },
  "additionalProperties": false
}

evidence_india

Read the 48-institution Indian construction-PIT crisis diagnostic, including misses and false alarms. Uses publication clocks where present and a +60-day filing-lag proxy otherwise; overwritten amendments are unreconstructable. evidence_institution returns a full replay.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

evidence_institution

Read a sourced Indian construction-PIT quarterly replay, lens alert timing and hit/miss/false-alarm verdict. Use evidence_india for exact slugs. Filing-availability proxies do not establish a validated backtest.

Parameters1

slug

string

required

kebab-case slug of a replayed institution, e.g. 'dhfl' or 'global-trust-bank'

Raw schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "kebab-case slug of a replayed institution, e.g. 'dhfl' or 'global-trust-bank'"
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false
}

evidence_markets

Historical evidence: India (48-institution construction-PIT diagnostic), US (industry-wide current-amended vintage), Europe (named cases, no cohort claim). Start here, then evidence_india, evidence_us or evidence_europe for details.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

evidence_us

Read US bank current-amended-vintage diagnostics and named replays, including misses. Not a validated point-in-time backtest. Report the quarterly top-decile budgeted watchlist beside recall, uncertainty and lead times; it is not an individual-bank verdict. include_trajectories:true adds histories.

Parameters1

include_trajectories

boolean

optional

also return per-quarter score series for the marquee replays (large payload); default false

Raw schema

{
  "type": "object",
  "properties": {
    "include_trajectories": {
      "type": "boolean",
      "description": "also return per-quarter score series for the marquee replays (large payload); default false",
      "default": false
    }
  },
  "additionalProperties": false
}

failure_radar_board

Read fresh-vetted Indian lender rows with failure PDs, disclosure, PCA/SAF, funding and listed-name DD. Scalar market_dd requires tier authority; display-only DD retains clocks and refusal reasons in market_dd_evidence. Discover slugs here, then failure_radar_institution. Research screen, not a credit rating.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

failure_radar_institution

Read one Indian lender dossier: quarterly PDs and drivers, PCA/SAF headroom, funding, forensic and listed-market evidence. Discover slugs with failure_radar_board. Uncovered institutions remain absent, never scored from memory.

Parameters1

slug

string

required

kebab-case institution slug from a failure_radar_board row, e.g. 'esaf-sfb'

Raw schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string",
      "description": "kebab-case institution slug from a failure_radar_board row, e.g. 'esaf-sfb'"
    }
  },
  "required": [
    "slug"
  ],
  "additionalProperties": false
}

forward_odds

Read counted Markov transitions and empirical 5/20-day reach odds. Odds are withheld until 60 observed days; counts stay visible and absence is never precision. Historical frequencies are not calibrated forecasts. Display-only, never a state driver.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

household_credit_board

Answers ONE question: is stress reaching US household credit? Use corporate_transmission_board for firms. Delinquency, charge-offs, revolving credit and unscored debt-service context; gaps stay in cannot_see. Display-only; no institution score or watchlist tier. full:true adds methods and histories.

Parameters1

full

boolean

optional

also return method_note, thresholds, labels and full sparklines (larger payload); default false

Raw schema

{
  "type": "object",
  "properties": {
    "full": {
      "type": "boolean",
      "description": "also return method_note, thresholds, labels and full sparklines (larger payload); default false",
      "default": false
    }
  },
  "additionalProperties": false
}

institution_research_coverage

Search Indian dossiers or RBI rows and evidence gaps. Populations overlap; do not infer identity or financial coverage from registry presence. Research only; no scoring.

Parameters4

scope	string	optional
q	string	optional
limit	integer	optional
offset	integer	optional

Raw schema

{
  "type": "object",
  "properties": {
    "scope": {
      "type": "string",
      "enum": [
        "dossiers",
        "rbi_registry"
      ]
    },
    "q": {
      "type": "string",
      "maxLength": 150
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 500
    },
    "offset": {
      "type": "integer",
      "minimum": 0,
      "maximum": 100000
    }
  },
  "additionalProperties": false
}

institution_review_packet

Build a compact cited human review packet from canonical fresh-vetted Indian radar records. Exact slug or uniquely normalized full name only; no fuzzy matching or new score. Preserves stale/dark gaps and validation hashes. Its content hash detects alteration; it is not attestation or a publication-time proof.

Parameters1

institution

string

required

exact Failure Radar slug or full institution name

Raw schema

{
  "type": "object",
  "properties": {
    "institution": {
      "type": "string",
      "description": "exact Failure Radar slug or full institution name"
    }
  },
  "required": [
    "institution"
  ],
  "additionalProperties": false
}

latest_article

Read today's exact full-text LiquiLens editorial: current institution-risk analysis when the evidence moved, or a labelled historical replay when it did not. Returns the canonical headline, dek, Markdown, evidence clock and passing publication receipt; quote it without regenerating facts.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

rbi_supervisory_tape

Read the latest RBI enforcement and supervisory actions — monetary penalties, licence cancellations and supervisory directions — parsed from rbi.org.in press releases, newest first, each item carrying the RBI's own source URL. Takes no arguments. When no tape snapshot exists on the deployment, says so in a stated note instead of returning silent emptiness.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

research_network

Route to Palimpsest sources, Seiche funding, Undertow exit liquidity and NarcoScope data. Set limit for full metadata. Rights remain attached; no identity, score or eligibility changes.

Parameters3

topic	string	optional
offset	integer	optional
limit	integer	optional

Raw schema

{
  "type": "object",
  "properties": {
    "topic": {
      "type": "string",
      "enum": [
        "all",
        "china",
        "regions",
        "information_controls",
        "model_evaluations",
        "funding",
        "institutions",
        "liquidity",
        "global_data"
      ],
      "default": "all"
    },
    "offset": {
      "type": "integer",
      "minimum": 0,
      "maximum": 1000,
      "default": 0
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 25,
      "default": 2
    }
  },
  "additionalProperties": false
}

stablecoin_rails_board

Read the compact Stablecoin Rails board: every tracked issuer's peg, redemption-run, direct-chain liability validation, coverage-gated reserve and executable-exit evidence, chain concentration and tripwire state plus the aggregate regime. Series and full receipts stay on the public REST detail route. Takes no arguments; the full oracle state never treats partial evidence as CALM (the separate peg/run alert is retained for compatibility), and the board is not investment advice.

Parameters

No parameters.

Raw schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

universe_search

Search the RBI NBFC register by name/CIN substring, classification or regulation layer. Returns official register rows. Supply q or a filter; a filter without q browses that slice. Registration does not establish creditworthiness.

Parameters4

q	string	optional	case-insensitive substring of the registered name or CIN
classification	string	optional	exact RBI classification as it appears in the register, e.g. 'MFI' or 'HFC'
layer	string	optional	Scale Based Regulation layer filter
limit	integer	optional	maximum rows to return (default 20, capped at 50)

Raw schema

{
  "type": "object",
  "properties": {
    "q": {
      "type": "string",
      "description": "case-insensitive substring of the registered name or CIN"
    },
    "classification": {
      "type": "string",
      "description": "exact RBI classification as it appears in the register, e.g. 'MFI' or 'HFC'"
    },
    "layer": {
      "type": "string",
      "enum": [
        "Upper",
        "Middle",
        "Base"
      ],
      "description": "Scale Based Regulation layer filter"
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 50,
      "description": "maximum rows to return (default 20, capped at 50)",
      "default": 20
    }
  },
  "additionalProperties": false
}

verify_published_record

Verify a ledger stream by recomputing hash-chain commitments and checking enabled signatures and anchors. Returns the actual verifier verdict, including failures. Verifies record integrity, not economic accuracy.

Parameters1

stream

string

optional

ledger stream name to verify (default 'mfi_watchlist')

Raw schema

{
  "type": "object",
  "properties": {
    "stream": {
      "type": "string",
      "description": "ledger stream name to verify (default 'mfi_watchlist')",
      "default": "mfi_watchlist"
    }
  },
  "additionalProperties": false
}

README.md16 KBView on GitHub

LiquiLens MCP — the Failure Radar as agent tools

Connect and ask one question

Hosted Streamable HTTP MCP; no local server or API key for public read-only tools. Add the products you need to Claude Code:

claude mcp add --transport http liquilens https://api.liquilens.in/mcp
claude mcp add --transport http seiche https://api.seiche.info/mcp
claude mcp add --transport http undertow https://api.seiche.info/undertow/mcp

Try this first: What changed in ESAF Small Finance Bank's NPAs? Cite the filing, reporting period and missing disclosures.

Try it in your browser · Cursor configuration · Codex commands · Free three-product starter kit and skill

For a connected review, ask for institution evidence → funding context → BTC exit estimates, with each source date, coverage gap and limitation kept separate. Client/model costs and fair-use limits may apply. Research calls do not execute trades.

Endpoint: https://api.liquilens.in/mcp (streamable HTTP, no auth, no install)

LiquiLens is the institution-evidence product of LIQUILENS PRIVATE LIMITED, a registered company in India (CIN U62011RJ2026PTC116792). One company, three connected products: LiquiLens investigates institutions, Seiche explains funding conditions, and Undertow examines market liquidity. People and AI agents can follow an exposure across all three while retaining each product's source dates, coverage gaps and research limits. International access does not imply universal market coverage or a shared score.

Read the company and investor story and the shared company profile.

Try it live: liquilens.in/developers · REST catalog: api.liquilens.in/api

LiquiLens is a failure early-warning system for banks and lenders, built on public data with a machine-readable historical-evidence boundary served beside every claim. Anonymous discovery on 11 October 2026 returned MCP 1.8.1 with 24 read-only tools and 5 guided prompts, so an agent reads the same status, eligibility flags and cited record a human sees. The repository contract retains its separately pinned source; discover the hosted endpoint for the current public inventory, including institution_evidence_monitor.

It now reads both ends of the chain: which institutions are fragile, and whether that stress is actually crossing into the real economy: companies rolling paper and drawing credit lines, households falling behind. Channels that cannot be read are named in cannot_see rather than reported as calm.

Add it

For Hermes and OpenClaw, use the native setup guides:

The current guides select thirteen research tools across LiquiLens, Seiche and Undertow, including GIFT City, reference FX and gold scenarios. Their dated native-client receipts retain the original nine-tool selection and exact verification scope. Public research requires no account or API key; fair-use limits apply and your model provider may charge separately.

The free starter kit also includes a Python brief, a manual n8n funding workflow and configurations for the clients below.

OpenClaw users can also install the optional research instructions from ClawHub:

openclaw skills install @beepboop2025/liquilens-trading-research --version 1.1.0

Connect the MCP servers using the OpenClaw guide first. The skill supplies task instructions and a configuration template; installation does not configure servers or run research. Its source bundle is MIT-0; that license does not relicense source data or API responses.

Checked on 4 October 2026 (UTC): version 1.1.0 is public and ClawHub's version-pinned verification result reports a passed security check with a benign, high-confidence verdict. Its embedded detailed scanner report retains seven findings, including medium external-transmission flags for the public MCP URLs, and reports partial analysis. Review the versioned security audit before installation and use public research inputs. Its isolated Linux install recorded the correct version and matched all three reviewed source files. ClawHub's public verifier and the installed Linux client's version-pinned openclaw skills verify now both report pass, with the generated Skill Card present. The upload is unsigned and has no server-resolved GitHub import provenance. A fresh isolated macOS install after storage recovery also matched all three source-file hashes, and its version-pinned verification reports pass. The earlier macOS timeout remains a separate failed attempt. No model or research tool ran in these checks. The direct MCP configuration is available independently of the ClawHub skill.

Claude Code:

code

claude mcp add --transport http liquilens https://api.liquilens.in/mcp

Codex:

code

codex mcp add liquilens --url https://api.liquilens.in/mcp

Cursor: merge the remote MCP config into .cursor/mcp.json for one project or ~/.cursor/mcp.json for all projects. The download includes the companion Seiche funding endpoint. Preserve existing entries. For an existing Codex config, use the TOML snippet and merge its server entries into ~/.codex/config.toml.

Claude.ai / ChatGPT: add a custom connector or MCP app with the endpoint above where that feature is available in your workspace.

This repository is the public discovery and documentation mirror. The hosted implementation is maintained in a private core repository. This public mirror pins its inspectable capability contract to the reviewed source revision above. The official Registry entry uses the name io.github.beepboop2025/liquilens. This repository's Registry metadata revision 1.8.1 points to the public mirror and free starter kit. The hosted MCP now reports version 1.8.1 at the same endpoint. The Registry metadata and runtime happen to share a version number; they remain separately verified contracts. The pinned source and tool inventory above describe the current runtime. The existing Registry record continues to identify this public mirror.

The current runtime separates fresh model results from reviewed filing facts: expired filing scores are excluded from the live board, current disclosures retain their official source and publication clocks, and inactive institutions remain identifiable in historical evidence. Its US evidence includes the June 2026 panel and reviewed 2026 failure notices through 25 September.

Query source histories

The separate source-data MCP and Python client expose funding histories, bank filings and Bitcoin/Liquid settlement observations with source receipts, native units and capture clocks. Use the live coverage table or import its OpenAPI contract.

Run a research task

The research recipes run with Python 3.11+ and its standard library. No API key, LLM or Python package install is needed. Download and inspect financial_research.py, then run:

python3 financial_research.py bank-review
python3 financial_research.py bank-review --slug cosmos-ucb
python3 financial_research.py funding-brief

The first command discovers covered bank slugs. The second checks coverage before retrieving that exact bank's sourced asset-quality history; an absent slug stays not_covered. The funding brief calls Seiche's money-market desk. Returned evidence retains its native source dates, eligibility, unavailable states and limitations; a successful request does not imply fresh or complete evidence. Each run is bounded and performs no scheduling or trading. Operators should add --verification so their checks are labelled synthetic and excluded from adoption totals.

For a visual workflow, download the n8n bank-review workflow and follow the import guide. It uses a manual trigger and no LLM. The guide records its execution-verification status; a downloadable workflow does not imply acceptance into n8n's template library.

Protocol compatibility

2026-07-28: stateless requests use server/discover, per-request _meta, MCP-Protocol-Version, and mirrored Mcp-Method / Mcp-Name routing headers.
2025-11-25, 2025-06-18, and 2025-03-26: retained legacy initialization, tools, prompts, notifications, batching, and ping behavior.
Tools, prompts, and discovery responses are deterministic. Modern list responses carry public cache metadata.
resources/list and resources/templates/list are supported and currently return empty catalogs. resources/read returns an explicit not-found error instead of inventing a resource.

Tools

Tool	What it serves
`bank_asset_quality_review`	Exact-slug bank review with sourced GNPA/NNPA history, percentage-point changes, distinct PCR definitions and capital/supervisory scope; no new score or credit approval
`bank_npa_reconciliation`	Arithmetic check of a complete caller-supplied NPA movement table; keeps cash recoveries, write-offs, sales and upgrades distinct without authenticating the input
`banking_specialisation_coverage`	Discover covered Indian commercial, small finance and urban cooperative banks, with observed, stale, historical and absent evidence distinguished; not a census or rating
`corporate_transmission_board`	Is funding stress reaching nonfinancial firms? The commercial-paper market, bank credit lines, real-economy confirmation (claims, capex, inventories, openings, business bankruptcies) and a balance-sheet context channel, with a TRANSMITTING/CONTAINED verdict
`crypto_exposure_board`	Cited bank/crypto exposure register joined to Undertow run-risk context; display-only, never an institution score
`crypto_regime_board`	Compact BTC/ETH change-point state and its display-only cross-read against disclosed bank exposure
`evidence_europe`	`NAMED_CASE_FILES_CONSTRUCTION_PIT`: seven audited case files, deliberately no cohort claim; both eligibility flags false
`evidence_india`	`PERIOD_END_PROXY_CONSTRUCTION_PIT`: 48 institutions across two decades, misses and false alarms included; both eligibility flags false
`evidence_institution`	One Indian institution's construction-PIT crisis replay with sourced quarterly rows
`evidence_markets`	Historical-evidence status for all three markets, with `validated_backtest_eligible` and `real_money_eligible` served explicitly
`evidence_us`	`CURRENT_AMENDED_CONSTRUCTION_PIT`: 552 FDIC failures since 2008, 72.8% recall, 21.7-month median lead and AUC 0.854; both eligibility flags false
`failure_radar_board`	The live board: every Indian lender with a fresh vetted dossier, including failure PD term structure (12/24/36m), RBI action-zone status, funding fragility, market distance to default, and watchlist tier under a published rule
`failure_radar_institution`	One institution in depth: PD trajectory with drivers, PCA/SAF headroom history, forensic screen, market reading
`forward_odds`	Counted forward stress odds for each public-signal layer, withheld until the layer has enough observed history
`household_credit_board`	Is stress transmitting through household balance sheets? Fed delinquency and charge-off legs against each leg's own trailing decade, two-sided revolving-credit velocity, debt service as unscored context
`institution_research_coverage`	Discover institution dossiers, registry entries and reviewed filing facts with separate observed, stale, historical, subset and registry-only states; coverage is not a rating or permission to trade
`institution_review_packet`	One lender's deterministic evidence packet for human review, with coverage and freshness stated explicitly
`latest_article`	Today's exact evidence-led LiquiLens article, or a labelled historical replay when the evidence did not move
`rbi_supervisory_tape`	Latest RBI enforcement actions, each linking to the RBI's own page
`research_network`	Bounded source discovery for connected Palimpsest, Seiche and Undertow research with availability and evidence boundaries intact
`stablecoin_rails_board`	Issuer peg, redemption-run, chain-concentration and rail tripwire state; missing data never becomes `CALM`
`universe_search`	RBI's official registered-NBFC registry (9,000+ entries)
`verify_published_record`	Independent cryptographic verification of the as-published record

Prompts

Prompt	Guided playbook
`bank_asset_quality_brief`	Discover an exact bank slug, review cited NPA history and capital scope, then reconcile only a complete disclosed movement table; preserve stale/missing evidence and supervisory gaps
`crypto_liquidity_briefing`	BTC/ETH regime, stablecoin rails, and disclosed bank links in one display-only evidence pack
`failure_radar_briefing`	Board-level institution risk with transmission context from the public US signal layers
`institution_health_check`	One lender health check with the historical-evidence boundary and uncertainty attached
`stress_evidence_pack`	Region-specific evidence for India, the United States, Europe, or the cross-market summary

The governance line

The generative layer explains; deterministic screening policy scores. Historical diagnostics retain their served evidence status and eligibility flags and do not become validated-backtest or real-money evidence merely because a deterministic engine produced them. Screens, not ratings; not investment advice. Institutions without a vetted dossier are absent by design — the tools say so rather than inventing a score.

The three historical status tokens are part of the API contract, not marketing copy: PERIOD_END_PROXY_CONSTRUCTION_PIT for India, CURRENT_AMENDED_CONSTRUCTION_PIT for the United States, and NAMED_CASE_FILES_CONSTRUCTION_PIT for Europe. In the current release, every market serves validated_backtest_eligible: false and real_money_eligible: false.

Siblings from the same lab

Seiche — US money-market funding stress (the plumbing)
groundcheck — claim grounding and citation verification
Palimpsest (https://api.seiche.info/palimpsest/mcp) — live internet-censorship signals
Undertow — the cross market liquidity map: daily tiered board, exit cost at position size, Telegram front door at t.me/undertow_LiquiLens_bot

Product: liquilens.in · Live demo: demo.liquilens.in

Quant research agent integrations

Native framework tools and cited quant pipeline captures connect Seiche funding, LiquiLens bank diagnostics and Undertow market liquidity through compact read-only tables. LangChain/LangGraph, CrewAI, OpenAI Agents and Pydantic AI share one evidence contract and repeat-call revision tokens. Current published history is not an as-published vintage archive. No execution authority or institutional-adoption claim is implied.

Install

Tools (23)

bank_asset_quality_reviewbank_npa_reconciliationbanking_specialisation_coveragecorporate_transmission_boardcrypto_exposure_boardcrypto_regime_boardevidence_europeevidence_india

Remote endpoint

Streamable HTTP

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

url

https://api.liquilens.in/mcp

Add to VS Code Add to Cursor

claude_desktop_config.json

json

{
  "mcpServers": {
    "liquilens": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://api.liquilens.in/mcp"
      ]
    }
  }
}

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

LiquiLens MCP — the Failure Radar as agent tools

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

Topics

bank_asset_quality_review

bank_npa_reconciliation

banking_specialisation_coverage

corporate_transmission_board

crypto_exposure_board

crypto_regime_board

evidence_europe

evidence_india

evidence_institution

evidence_markets

evidence_us

failure_radar_board

failure_radar_institution

forward_odds

household_credit_board

institution_research_coverage

institution_review_packet

latest_article

rbi_supervisory_tape

research_network

stablecoin_rails_board

universe_search

verify_published_record

LiquiLens MCP — the Failure Radar as agent tools

Connect and ask one question

Add it

Query source histories

Run a research task

Protocol compatibility

Tools

Prompts

The governance line

Siblings from the same lab

Quant research agent integrations

Install

Remote endpoint

Related servers