SEC Intelligence

{
  "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
  "name": "io.github.jahanv01/sec-intelligence-mcp",
  "description": "SEC 10-K/10-Q/8-K search, RAG Q&A, comparison, and anomaly detection with citations.",
  "title": "SEC Intelligence",
  "repository": {
    "url": "https://github.com/jahanv01/sec-intelligence-mcp",
    "source": "github"
  },
  "version": "0.1.1",
  "packages": [
    {
      "registryType": "pypi",
      "registryBaseUrl": "https://pypi.org",
      "identifier": "sec-intelligence-mcp",
      "version": "0.1.1",
      "runtimeHint": "uvx",
      "transport": {
        "type": "stdio"
      },
      "environmentVariables": [
        {
          "description": "Google Gemini API key (free tier). Get one at https://aistudio.google.com/apikey",
          "isRequired": true,
          "isSecret": true,
          "name": "GEMINI_API_KEY"
        },
        {
          "description": "Qdrant vector database URL, e.g. http://localhost:6333 for local Docker, or a Qdrant Cloud cluster URL",
          "isRequired": true,
          "name": "QDRANT_URL"
        },
        {
          "description": "Only needed for a hosted Qdrant Cloud instance; leave unset for local Qdrant",
          "isSecret": true,
          "name": "QDRANT_API_KEY"
        },
        {
          "description": "LangFuse secret key for observability (free tier). Get one at https://cloud.langfuse.com",
          "isRequired": true,
          "isSecret": true,
          "name": "LANGFUSE_SECRET_KEY"
        },
        {
          "description": "LangFuse public key, paired with LANGFUSE_SECRET_KEY",
          "isRequired": true,
          "name": "LANGFUSE_PUBLIC_KEY"
        },
        {
          "description": "Identifying User-Agent for SEC EDGAR requests, e.g. \"YourApp you@email.com\"",
          "default": "sec-intelligence-mcp dev@example.com",
          "name": "SEC_EDGAR_USER_AGENT"
        },
        {
          "description": "sentence-transformers model for embeddings",
          "default": "intfloat/e5-base-v2",
          "name": "EMBEDDING_MODEL"
        },
        {
          "description": "Gemini model for answer generation",
          "default": "gemini-flash-lite-latest",
          "name": "GEMINI_MODEL"
        }
      ]
    }
  ]
}