SEC 10-K/10-Q/8-K search, RAG Q&A, comparison, and anomaly detection with citations.
SEC Intelligence is an MCP integration. SEC 10-K/10-Q/8-K search, RAG Q&A, comparison, and anomaly detection with citations.
The published pypi package is sec-intelligence-mcp, version 0.1.1. Its declared MCP transport is stdio.
The package declares GEMINI_API_KEY (required): Google Gemini API key (free tier). Get one at https://aistudio.google.com/apikey; QDRANT_URL (required): Qdrant vector database URL, e.g. http://localhost:6333 for local Docker, or a Qdrant Cloud cluster URL; QDRANT_API_KEY: Only needed for a hosted Qdrant Cloud instance; leave unset for local Qdrant; LANGFUSE_SECRET_KEY (required): LangFuse secret key for observability (free tier). Get one at https://cloud.langfuse.com; LANGFUSE_PUBLIC_KEY (required): LangFuse public key, paired with LANGFUSE_SECRET_KEY; SEC_EDGAR_USER_AGENT: Identifying User-Agent for SEC EDGAR requests, e.g. "YourApp you@email.com"; EMBEDDING_MODEL: sentence-transformers model for embeddings; GEMINI_MODEL: Gemini model for answer generation.
Check the maintainer’s instructions for account access, authentication and the supported client configuration. Once connected, inspect the tools your client receives and try a small task that matches the server’s stated purpose. The registry description does not include a verified, complete tool list.
View the publisher’s registry entry · Project repository. This profile uses version 0.1.1 from the registry. Registration identifies the publisher namespace; it does not establish that this is a first-party integration for every service it connects.
Browse related other integrations MCP servers for tools that cover the same kind of work.
| Variable | Description | Required |
|---|---|---|
| GEMINI_API_KEY | Google Gemini API key (free tier). Get one at https://aistudio.google.com/apikey | Yes |
| QDRANT_URL | Qdrant vector database URL, e.g. http://localhost:6333 for local Docker, or a Qdrant Cloud cluster URL | Yes |
| QDRANT_API_KEY | Only needed for a hosted Qdrant Cloud instance; leave unset for local Qdrant | Optional |
| LANGFUSE_SECRET_KEY | LangFuse secret key for observability (free tier). Get one at https://cloud.langfuse.com | Yes |
| LANGFUSE_PUBLIC_KEY | LangFuse public key, paired with LANGFUSE_SECRET_KEY | Yes |
| SEC_EDGAR_USER_AGENT | Identifying User-Agent for SEC EDGAR requests, e.g. "YourApp you@email.com" | Optional |
| EMBEDDING_MODEL | sentence-transformers model for embeddings | Optional |
| GEMINI_MODEL | Gemini model for answer generation | Optional |
Official Redis server — search keys, inspect data structures and manage caches in natural language.
Enables AI agents and LLMs to interact with the web and extract information from web pages via the RAG Web Browser Actor.
Enables semantic search and retrieval of documentation using a vector database, allowing users to add and query documentation from URLs or local
Augments AI responses with relevant documentation context through vector search.
Augment AI responses with context by retrieving and processing documentation through vector search.
Enables semantic analysis of chat conversations through vector embeddings and knowledge graphs.