An MCP server that provides semantic search over a document corpus, enabling AI clients to retrieve and cite relevant chunks from indexed documents via RAG pipelines.
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process.env. You'll be asked to provide them before it can run.DOCQA_STORE— export =pgvector DATABASE_URL=postgresql://docqa:docqa@localhost:5432/docqaDOCQA_SQLITE_PATHDATABASE_URL— export DOCQA_STORE=pgvector =postgresql://docqa:docqa@localhost:5432/docqaDOCQA_EMBEDDINGS— Semantic embeddings — put an OpenAI key in .env (see [.env.example](.env.example)) and re-index; =auto picks it up:OPENAI_API_KEYDOCQA_OPENAI_EMBEDDING_MODEL[](https://m8ven.ai/mcp/saivarun161-mcp-docqa-server-1litb0)