Scholar RAG MCP Server

Scholar RAG MCP is an MCP integration. Academic paper knowledge-base MCP server: PDF ingest, vector search with reranking, KB management.

Packages and local setup

The published pypi package is scholar-rag-mcp, version 0.4.0. Its declared MCP transport is stdio.

The package declares SCHOLAR_RAG_DATA_DIR: Data root directory (knowledge bases, caches, jobs); SCHOLAR_RAG_CHAT_BASE_URL (required): OpenAI-compatible chat endpoint for annotation/keywords (e.g. local vLLM); SCHOLAR_RAG_EMBED_BASE_URL (required): OpenAI-compatible embeddings endpoint; SCHOLAR_RAG_RERANK_BASE_URL (required): Rerank endpoint (/v1/rerank).

Before connecting

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.

Project and source

View the publisher’s registry entry · Project repository. This profile uses version 0.4.0 from the registry. Registration identifies the publisher namespace; it does not establish that this is a first-party integration for every service it connects.

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