The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Signaldaemon listing page.
Narrative & signal intelligence for AI agents — crypto, AI, and macro. A dumb-but-trustworthy pipe: it delivers curated narrative & signal, not raw data, and it fails safe — when it has no coverage it says so, rather than inventing. Built for machines, not human eyes.
https://api.signaldaemon.comPOST /v1/request-key (no signup)This repo is the front door — quickstart, client configs, and the interface contract. The pipeline itself (sources, scoring, curation) is not open source.
| It is | It is not |
|---|---|
| Cross-source narrative convergence + capital-vs-narrative divergence | A price/market-data API (use CoinGecko etc. for that) |
| Coverage across ~14 crypto/AI/macro domains | A raw news firehose |
| Fails safe — "no coverage" over hallucination | A database you query for facts |
| For agents (API/MCP), token-cost-agnostic, quality-first | A human-facing dashboard |
Remote MCP over Streamable HTTP, authenticated with the x-api-key header.
More clients (Cursor, Cline) in examples/mcp-configs.md.
Tools: get_market_narratives(limit) · get_clean_feed(query, category, limit) ·
vet_trade(symbol, side) — all annotated readOnlyHint. vet_trade is the
pre-trade gate: hand it a candidate trade and it returns a narrative-layer stance
(support/caution/contradict/no_signal) with reason + confidence — it vets,
it does not recommend.
For clients that don't support remote MCP, this repo ships a thin stdio
bridge (mcp_server.py) exposing the same three tools over
the hosted API. It holds no methodology — just a client.
Or with Docker:
The bridge starts and answers introspection (tools/list) without a key;
tool calls require one.
Endpoints and response-field contract (incl. the divergence schema) in
API.md. Field names are stable.
Examples and docs in this repo: MIT (see LICENSE). The signaldaemon service and pipeline are proprietary.