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CausalLayer MCP Server

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CausalLayer MCP is answering right now. Last checked 12 min ago. 28 installs a week from npm. It exposes 10 tools. Last commit 8 Jun 2026.

Deterministic AI liability attribution with Bitcoin-anchored proof certificates.

Installs per day peak 13 · avg 3 · -12% w/w
a month agotoday
Uptime history 47 days of history
47 days agonow
100.0%
Uptime 24h
91 of 91 checks
10
Tools
read from the server
894 ms
Response time
average over 24h
28
Installs / week
npm and PyPI

What the code does

We read the source, 19 h ago · tools taken from the live server · rules 3dff92dd89df

Capabilities

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

Runs an external command cli/bin/causallayer-mcp.mjs:100
const child = spawn(cmd, cmdArgs, {

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

This code can reach further than it looks

We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 12 min ago.

run in your terminal
claude mcp add causallayer --transport http https://mcp.faultkey.com/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "causallayer": {
      "url": "https://mcp.faultkey.com/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.causallayer]
url = "https://mcp.faultkey.com/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "causallayer": {
      "url": "https://mcp.faultkey.com/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "causallayer": {
      "url": "https://mcp.faultkey.com/mcp"
    }
  }
}

Available tools 10

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

submit
submit_incident
Submit an AI incident for deterministic causal liability attribution. Returns a signed CausalCertificate, per-agent liability allocation, evidence-chain completeness, regulatory mapping, and (where keys are configured) a Bitcoin-anchored proof. Cost: 50 credits. Three guardrails apply: PII scan, deterministic-only acknowledgement, and minimum evidence.
submit_otel_trace
Convert an OpenTelemetry OTLP JSON trace into a FaultKey incident and return the same deterministic CausalCertificate as submit_incident. Each span becomes an event; service.name groups spans into agents; W3C trace_id and span_id propagate as evidence pointers on the causal graph edges. Cost: 50 credits (same as submit_incident). Three guardrails apply: PII scan, deterministic-only acknowledgement, and minimum evidence (auto-satisfied when the trace has at least 1 span).
verify
verify_certificate
Independently verify a CausalCertificate end-to-end (signature, Merkle integrity, issuer status against the registry). Cost: 1 credit. In production env, certificates from non-active issuers are rejected.
verify_certificate_recompute
Independently re-derive a CausalCertificate from its canonical input and compare byte-for-byte against the claimed certificate. This is the strongest verification path: it requires no trust in the issuer or signing key. Cost: 1 credit (same price as verify_certificate). Returns PASS only if every checked field (certificateId, request_hash, merkleRoot, verdict, causalGraph, fourFactorScoring, deviationTaxonomy, euRuleOverlay, cascadeAttenuation, damages, underwriting) matches identically.
anchor
get_anchor_status
Return the index of all CausalLayer Tessera anchor batches, or one batch's full JSON (signed Merkle root, leaves, OpenTimestamps proof reference). FREE.
evaluate
evaluate_prospective_response
Deterministic prospective-evaluation gate (FK-METHOD-2026-006). Pass a ProposedAction BEFORE the agent delivers a response; receive one of three verdicts: 'allow', 'require_revision' (with specific factor-keyed directives), or 'block'. Uses the same four-factor engine that issues post-hoc certificates, so a single incident chains: prospective_pre_image -> response -> certificate -> anchor. This is a policy gate on structured action metadata, NOT a content safety classifier on raw prose. Thresholds are per-jurisdiction (EU strictest, US most permissive); read via GET /api/v2/gate/thresholds. Overrides are allowed but REQUIRE a governance rationale so the audit trail is complete. Cost: 1 credit. Pure deterministic.
extract
extract_incident
Claude-powered structured extractor. Parses unstructured text (news articles, court filings, emails, PDFs, incident reports, logs) into the typed JSON schema required by submit_incident. Returns a ready-to-submit incident object with extracted agents, events, severity, jurisdiction, and financial impact. NOTE: This is a pre-processing convenience tool — the deterministic scoring engine itself remains LLM-free. Cost: 10 credits.
issuer
query_issuer_registry
Return the CausalLayer issuer registry, or one issuer record. The registry lists all trusted public-key fingerprints, key algorithms, validity windows, and the anchor-log repo for each active issuer. FREE — no API key required.
jurisdiction
query_jurisdiction_overlay
Multi-jurisdiction overlay (FK-METHOD-2026-004). Given a canonical attributable apportionment (party-id -> share), the union of all jurisdiction role tags on each actor, and the union of jurisdiction-specific flags, return side-by-side post-overlay shares for AU, EU, US, UK, CA (or a chosen subset) with the specific rules that fired in each, citation URLs, and a parties × jurisdictions matrix. v1 ships full implementations for AU and EU; US/UK/CA are research stubs marked `is_stub: true`. Use GET /api/v2/jurisdiction/catalog to discover support and stub status. Cost: 1 credit. Pure deterministic.
simulate
simulate_remediation
Counterfactual remediation simulator. Given a certificate's verdict + fourFactorScoring + agents and a list of remediation IDs from the FK-METHOD-2026-003 catalog, return the apportioned shares each remediation would have produced (in isolation) and the composite shares if they all stack. Every remediation cites a specific statute or standard. GET /api/v2/remediation/catalog for the list of IDs. Cost: 1 credit (same price as verify_certificate). Pure deterministic; same inputs produce a byte-identical result.

Endpoints

URLTransportStateLatencyChecked
https://mcp.faultkey.com/mcp streamable-http answering 850 ms 12 min ago

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CausalLayer MCP — questions

Answers built from our own checks of this server.

What can CausalLayer MCP do?
It exposes 10 tools, read directly from the server on our last check. Among them: evaluate_prospective_response, extract_incident, get_anchor_status, query_issuer_registry, query_jurisdiction_overlay, simulate_remediation and 4 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
What is CausalLayer MCP mostly used for?
Its tools cluster around submit and verify. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is CausalLayer MCP working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 894 ms. The bar chart above shows every period we have measured.
How do I connect CausalLayer MCP?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does CausalLayer MCP need an API key?
No. CausalLayer MCP completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 10 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is CausalLayer MCP?
It answers our handshake in 894 ms on average, which is faster than 11% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.
How many people use CausalLayer MCP?
The npm package causallayer-mcp was installed 28 times in the last week. Week over week that is -12%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.
Is CausalLayer MCP open source?
Yes — it is published under the Apache-2.0 licence, written in TypeScript, 2 stars on GitHub and 21 open issues. The source link is on this page, so you can read exactly what it does with your data before you connect it.