casuallayer-mcp
Deterministic AI liability attribution engine. Scores fault across AI supply-chain participants (deployer, developer, vendor) with tamper-evident certificates and weekly cryptographic anchoring.’
README
FaultKey · CausalLayer MCP Server
<p align="center"> <img src="./demo.svg" alt="FaultKey CausalLayer MCP — terminal demo showing liability attribution" width="820" /> </p>
Deterministic fault math for multi-party AI incidents. When an AI causes harm and three parties argue over who pays, FaultKey returns a signed, Bitcoin-anchored certificate of fault allocation in under 200 ms — no LLM, no probabilistic scoring, no vendor cooperation needed for a third party to verify.
This is the official Model Context Protocol (MCP) server for the CausalLayer engine, packaged as a Cloudflare Worker. It lets AI agents (Claude Desktop, Cursor, Cline, Continue, Windsurf) call the four core liability-attribution tools without writing a single line of integration code.
If this saves you time, give it a star — it helps others find it and tells us people care.
Live demo
🎮 Try the Interactive Demo — No setup required. Pick a scenario, click "Run Analysis", see real-time liability attribution.
The public Worker is deployed on Cloudflare's global edge network and is fully functional in standalone demo mode (deterministic responses, watermarked, rate-limited 5 calls / IP / day):
- Endpoint:
https://mcp.faultkey.com/mcp(live, custom domain) - Mirror:
https://causallayer-mcp-demo.zykm9qkk7j.workers.dev/mcp - Healthcheck:
/healthz - Demand telemetry:
/stats(public, aggregated, no PII)
Quick start
Claude Desktop
Add this to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"faultkey": {
"command": "npx",
"args": ["-y", "causallayer-mcp"]
}
}
}
Restart Claude. Type "List the FaultKey tools."
Cursor
Settings → MCP Servers → Add new:
- Name:
faultkey - Command:
npx -y causallayer-mcp
Cline / Continue / Windsurf
{
"name": "faultkey",
"command": "npx",
"args": ["-y", "causallayer-mcp"]
}
Direct HTTP (no CLI)
curl -X POST https://causallayer-mcp-demo.zykm9qkk7j.workers.dev/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json, text/event-stream" \
-d '{"jsonrpc":"2.0","id":0,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"test","version":"0"}}}'
The response includes a Mcp-Session-Id header that you reuse for subsequent calls.
Tools
| Tool | Description | Demo limit | Paid cost |
|---|---|---|---|
submit_incident |
Submit an AI incident for deterministic liability attribution. Returns a signed CausalCertificateV1 with per-agent fault allocation, evidence-chain completeness, and Bitcoin-anchored proof. |
5 / IP / day | 50 credits |
verify_certificate |
Independently verify a certificate (signature, Merkle integrity, issuer status) without calling FaultKey. | 50 / IP / day | 1 credit |
get_anchor_status |
Return the index of all Tessera anchor batches or one batch's full JSON (signed Merkle root, OpenTimestamps proof reference). | Unlimited | Free |
query_issuer_registry |
List all trusted CausalLayer issuer public-key fingerprints, status, and validity windows. | Unlimited | Free |
Why deterministic?
Insurers, banks, and APRA-regulated entities cannot accept LLM-based fault attribution because the same prompt produces different answers on different days. FaultKey uses a closed-form causal scoring algorithm (graph-theoretic, version-pinned, byte-identical reproducible across runs) so two adversarial parties get the same number — that's the whole point.
The math is published as an Australian Standards-aligned paper. The signed certificate, issuer registry, and Merkle anchor log are all independently verifiable by a third party using only Node's built-in crypto and the causallayer-verifier tool — no network calls back to the vendor.
Guardrails (enforced at the Cloudflare edge)
- NO-PII — Payloads are regex-scanned for emails, Tax File Numbers, Medicare numbers, SSNs, and credit cards. Rejected unless the caller sets
pii_acknowledged: true(which is logged in the certificate as a compliance acknowledgement). - DETERMINISTIC-ONLY — The engine rejects any request lacking
deterministic_only: true. This is the agent's binding acknowledgement that FaultKey output is closed-form, not probabilistic. - EVIDENCE-REQ — At least one identified agent and one timestamped event with description must be supplied or the request is rejected with
400 evidence_insufficient.
Self-hosting
You can deploy your own copy to your own Cloudflare account if you want to enforce a corporate firewall, custom rate limits, or bring your own KV namespace:
git clone https://github.com/smq9sn5jck-coder/causallayer-mcp.git
cd causallayer-mcp
pnpm install
pnpm wrangler kv namespace create LEDGER
# paste the returned id into wrangler.jsonc
pnpm wrangler deploy
The CausalLayer engine itself (the closed-form fault math) runs upstream and is available via API key. For self-hosted demos without an upstream, set STANDALONE_DEMO=true in wrangler.jsonc to short-circuit upstream calls and return deterministic, watermarked responses.
Architecture
[Claude/Cursor/Cline] ←→ [npx causallayer-mcp] ←→ [Cloudflare Worker] ←→ [CausalLayer engine]
(mcp-remote proxy) (this repo) (Fly.io Sydney)
↓
[KV: credit ledger]
[DO: per-session state]
[KV: telemetry buffer]
- Transport: Streamable HTTP (per the 2024-11-05 MCP spec — SSE is deprecated)
- Session state: Cloudflare Durable Object (
CausalLayerMCP), SQLite-backed - Billing: Cloudflare KV ledger, Stripe Checkout webhook, optional x402 USDC fallback
- Demo: Per-IP daily counter in KV, deterministic fixture responses with
[DEMO]watermark - Latency: p50 ≈ 60 ms (cold), 25 ms (warm) on Cloudflare's 300+ POPs
Pricing
| Tier | Credits | $AUD | Notes |
|---|---|---|---|
| Demo | 5 incidents / IP / day | Free | Watermarked responses |
| Starter | 1,000 | $99 | Stripe Checkout, no SLA |
| Growth | 10,000 | $749 | + 50 verify, 99.5% SLA |
| Enterprise | Unmetered | Contact | + dedicated namespace, 99.95% SLA, audit log access |
For enterprise tenants email sales@faultkey.com (or open a GitHub issue with subject "enterprise inquiry").
Free AI Liability Risk Assessment
Not sure where your AI liability exposure sits? Take the free FaultKey AI Liability Risk Assessment — 2 minutes, no sales call, instant preliminary risk score. Covers EU AI Act, APRA CPS 230, and NIST AI RMF.
License
Apache 2.0. See LICENSE.
Support the Project
If FaultKey helped you understand AI liability, saved you research time, or you just think deterministic fault attribution should exist:
- Star this repo — github.com/smq9sn5jck-coder/causallayer-mcp
- Share it — post on LinkedIn, X, or your team Slack
- Try the demo — Interactive Demo
- Take the free assessment — AI Liability Risk Assessment
Built in Brisbane
FaultKey is built in Brisbane, Australia, with data residency in Sydney for APRA-regulated buyers. The team can be reached at hello@faultkey.com.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.