Schema | rag-mcp

rag-mcp

Describes the environment variables required to run the server.

Name	Required	Description	Default
`RAG_MCP_DB_PATH`	Yes	Path to the ChromaDB persistent directory
`RAG_MCP_EMBEDDER`	No	Embedder model to use: 'miniLM' (default) or 'bge'	miniLM
`RAG_MCP_COLLECTION`	Yes	Name of the ChromaDB collection
`RAG_MCP_CORPUS_ROOT`	Yes	Root directory of the corpus (auth scope)

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{ "listChanged": false }
`experimental`	{}

Functions exposed to the LLM to take actions

Name	Description
search_knowledgeA	Retrieve the most relevant passages from the configured knowledge corpus for a natural-language query. Returns the passage text plus a CITATION (source file + heading + chunk index) for each hit so answers are traceable. Auth-scoped to the corpus root and fail-soft: a down/empty store returns a structured error, never an exception. Use when asked to look something up in the knowledge base / docs.

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

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curl -X GET 'https://glama.ai/api/mcp/v1/servers/jaimenbell/rag-mcp'

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