Finds and ranks retrieval-focused MCP servers by domain, transport, reachability, citations, privacy, and other constraints.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ we're steadily working through the catalog.
๐ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Ragmap.
The khalidsaidi/ragmap MCP server is a discovery and routing layer for retrieval-oriented MCP servers. It maintains a focused subregistry based on the official MCP Registry, adds metadata useful for RAG selection, and exposes search and inspection interfaces for agents and developers.
The project does not retrieve documents, manage a private vector database, or ingest a user's files. Instead, it returns candidate servers and connection information so an agent can connect to a selected retrieval server for the actual search or generation workflow.
A hosted service is available at https://ragmap-api.web.app, including a browser interface and MCP endpoint. The repository also supports local development and a local stdio MCP package.
Registry records are normalized and enriched with fields such as domain coverage, retrieval approach, freshness behavior, grounding or citation support, privacy and authentication characteristics, transport, and usage limits. Lightweight trust signals include service status, recent reachability checks, schema stability, and reports.
Agents can search or filter the catalog by query, categories, minimum score, transport, registry type, remote availability, recent reachability, citation metadata, or local-only operation. The service can combine keyword search with semantic search when OPENAI_API_KEY is configured. Results include ranking information, and rag_explain_score can provide reasons behind a score.
The MCP interface exposes four tools: rag_find_servers, rag_get_server, rag_list_categories, and rag_explain_score. The REST API provides related endpoints for search, top recommendations, installation details, categories, statistics, health, and registry-compatible server records.
For a hosted connection, the README gives this Claude MCP command:
The hosted deployment can be queried directly with HTTP. For example, /rag/search supports filters for recent reachability and remote availability, while /rag/install returns installation configuration for a selected server.
To run the local MCP package over stdio, use:
Local repository development uses corepack enable, pnpm -r install, and pnpm -r dev. The API runs on port 3000 and the local remote MCP service on port 4000. Semantic search is optional; setting OPENAI_API_KEY enables it locally. Self-hosted ingestion uses a protected X-Ingest-Token and is intended for operators managing their own index schedule.
The khalidsaidi/ragmap MCP server is useful for routing decisions where backend choice depends on constraints such as privacy, citations, freshness, or deployment transport.
Index updates occur on a schedule in the hosted deployment, so new or changed servers may not appear immediately. Reachability is based on probe checks for streamable HTTP or SSE endpoints and may become stale. Semantic search depends on an OpenAI API key; without it, keyword search remains available.
The khalidsaidi/ragmap MCP server does not replace an end-to-end RAG pipeline. It does not automatically ingest private documents, host a user's vector store, or perform retrieval on behalf of the caller. Users must connect to a returned retrieval server, or provide another server that supports their ingestion and indexing process.
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