SEC Intelligence
io.github.jahanv01/sec-intelligence-mcp
SEC 10-K/10-Q/8-K search, RAG Q&A, comparison, and anomaly detection with citations.
Connect this server
Add this to your MCP client config — claude_desktop_config.json (Claude Desktop) or .cursor/mcp.json (Cursor).Suits: Claude Desktop · Cursor.
{
"mcpServers": {
"sec-intelligence-mcp": {
"command": "uvx",
"args": [
"sec-intelligence-mcp"
],
"env": {
"GEMINI_API_KEY": "<your GEMINI_API_KEY>",
"QDRANT_URL": "<your QDRANT_URL>",
"QDRANT_API_KEY": "<your QDRANT_API_KEY>",
"LANGFUSE_SECRET_KEY": "<your LANGFUSE_SECRET_KEY>",
"LANGFUSE_PUBLIC_KEY": "<your LANGFUSE_PUBLIC_KEY>",
"SEC_EDGAR_USER_AGENT": "sec-intelligence-mcp dev@example.com",
"EMBEDDING_MODEL": "intfloat/e5-base-v2",
"GEMINI_MODEL": "gemini-flash-lite-latest"
}
}
}
}- GEMINI_API_KEYrequiredsecretGoogle Gemini API key (free tier). Get one at https://aistudio.google.com/apikey
- QDRANT_URLrequiredQdrant vector database URL, e.g. http://localhost:6333 for local Docker, or a Qdrant Cloud cluster URL
- QDRANT_API_KEYsecretOnly needed for a hosted Qdrant Cloud instance; leave unset for local Qdrant
- LANGFUSE_SECRET_KEYrequiredsecretLangFuse secret key for observability (free tier). Get one at https://cloud.langfuse.com
- LANGFUSE_PUBLIC_KEYrequiredLangFuse public key, paired with LANGFUSE_SECRET_KEY
- SEC_EDGAR_USER_AGENTIdentifying User-Agent for SEC EDGAR requests, e.g. "YourApp you@email.com"
- EMBEDDING_MODELsentence-transformers model for embeddings
- GEMINI_MODELGemini model for answer generation
A starting point — check the repository for exact arguments and setup. Restart your client after editing the config.
- Category
- Developer Tools
- Version
- 0.1.1
- Registry
- active
- Published
- 9/12/2026
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HTML — for your website
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Markdown — for your README
[](https://serverdex.io/server/io-github-jahanv01-sec-intelligence-mcp?utm_source=badge)Nice for visibility, but GitHub marks README links nofollow, so it doesn't pass authority. Use the HTML badge on your site as well.