The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Catalyst Edge MCP listing page.
Publicly graded SEC catalyst intelligence for AI agents, over the Model Context Protocol. Every US-market SEC filing with market-moving potential is fetched from EDGAR, scored by 500+ data engines, and ranked before the market opens — and unlike most signal products, the track record is public: every past call is published with its outcome at catalystedgescanner.com/receipts.
A hosted instance is live. Point any MCP-capable client at it, or POST JSON-RPC directly:
Call a tool (no key needed for the free tier):
Paid tiers use a Bearer token: Authorization: Bearer <your-key>.
| Tool | Tier | Returns |
|---|---|---|
get_convergence_picks | free | today's scored catalyst picks (free: top 3) |
get_track_record | free | historical hit-rate / alpha of published picks |
get_ticker_signal | intelligence | full per-ticker signal-layer breakdown |
get_thesis | intelligence | plain-language thesis (catalysts, risks, bear case) |
get_sector_lean | intelligence | directional sector lean |
free — evaluation tier, no key required. intelligence — all tools, full depth; keys via catalystedgescanner.com/pricing or catalystedgepro@gmail.com.
Stdlib Python only — no dependencies. HTTP mode: CATALYST_MCP_HTTP=1 python3 catalyst_mcp.py (binds 127.0.0.1:8848; front with TLS for public use — see catalyst-mcp.service). Key→tier mapping lives in mcp_keys.json (see mcp_keys.json.example).
Sources: SEC EDGAR (filings, XBRL, insider activity), US government open data, delayed market prices. Nothing here is financial advice; signals are research with a published, self-graded track record — hits and misses both, each measured against the next session's open. Machine-readable site map: catalystedgescanner.com/llms.txt · OpenAPI: /openapi.json.
MIT licensed.