RAG-MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| RAG_CORPUS_DIR | Yes | Path to the directory of Markdown and text documents to index. |
Instructions
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.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_documentsA | Search the indexed corpus for passages relevant to a query and return ranked results with their source file and a snippet. Use this first, then call get_chunk or get_document to read the full text of anything you intend to quote or rely on. |
| get_chunkA | Return the full text of one passage by its chunk id, as returned by search_documents, together with its character offsets in the source file. |
| get_documentA | Return the full text of one indexed document by its source path. Large documents are truncated, and the response says so. |
| list_documentsA | List every indexed document with its size and chunk count. Use it to find out what this corpus actually covers before searching. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: search returns ranked passages, get_chunk retrieves a specific chunk, get_document retrieves a full document, and list_documents provides an overview. There is no overlap or ambiguity between them.
All tool names follow the same verb_noun pattern with lowercase and underscores: search_documents, get_chunk, get_document, list_documents. The convention is perfectly consistent.
Four tools form a tight, well-scoped set for a RAG server. Each tool earns its place by covering the essential retrieval workflow without redundancy or bloat.
The tool surface covers the full retrieval lifecycle: discover what's indexed (list_documents), search the corpus (search_documents), read a specific passage (get_chunk), and read the full source (get_document). No obvious gaps exist for the stated purpose.