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Deterministic AI liability attribution with Bitcoin-anchored proof certificates.
Deterministic AI liability attribution with Bitcoin-anchored proof certificates.
Remote endpoints: streamable-http: https://mcp.faultkey.com/mcp
Valid MCP server (2 strong, 2 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
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Available as Local & Remote
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From the project's GitHub README.
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.
🎮 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):
https://mcp.faultkey.com/mcp (live, custom domain)https://causallayer-mcp-demo.zykm9qkk7j.workers.dev/mcp/healthz/stats (public, aggregated, no PII)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."
Settings → MCP Servers → Add new:
faultkeynpx -y causallayer-mcp{
"name": "faultkey",
"command": "npx",
"args": ["-y", "causallayer-mcp"]
}
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.
| 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 |
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.
pii_acknowledged: true (which is logged in the certificate as a compliance acknowledgement).deterministic_only: true. This is the agent's binding acknowledgement that FaultKey output is closed-form, not probabilistic.400 evidence_insufficient.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.
[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]
CausalLayerMCP), SQLite-backed[DEMO] watermark| 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").
Score any AI incident in seconds — faultkey.com/score — describe what happened, get a deterministic liability split with dollar exposure, jurisdiction analysis, and a shareable verdict card.
Compare vendor liability profiles — faultkey.com/compare — side-by-side comparison of AI vendors (OpenAI vs Anthropic vs Google etc.) across incident types.
Public accuracy ledger — faultkey.com/track-record — 7/7 direction match on backtested cases, 3 pending predictions on active litigation.
Apache 2.0. See LICENSE.
If FaultKey helped you understand AI liability, saved you research time, or you just think deterministic fault attribution should exist:
FaultKey is built in Brisbane, Australia, with data residency in Sydney for APRA-regulated buyers. The team can be reached at hello@faultkey.com.
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