RAG MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| retrieve_documentsA | Retrieve relevant research paper chunks for a query using semantic search over a corpus of arXiv papers. |
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 1 tool
Only one tool exists, so there is no possibility of confusion between tools. The single tool's purpose is clear and distinct by default.
With only one tool, naming is trivially consistent. 'retrieve_documents' follows a clear verb_noun pattern and is appropriately descriptive.
A single tool is too few for a server advertised as a RAG server. RAG typically requires document ingestion, indexing, and management in addition to retrieval, so the tool count is inadequate for the apparent scope.
The tool surface is severely incomplete for a RAG workflow. There is no way to add, update, or delete documents in the corpus, nor any indexing or management operations, leaving only retrieval with no supporting lifecycle.