RAG MCP Tool
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| RAG_MCP_CONFIG | No | Path to the config.yaml file for RAG MCP configuration |
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 |
|---|---|
| search_ragC | Search for keyword in RAG database. Args: keyword: Search query. dir_path: Optional directory to search in. If None, searches all indexed directories. |
| read_raw_fileB | Read raw content of a file. Args: file_path: Absolute path to the file. |
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 2 tools
The two tools have completely distinct purposes: one reads raw file content, while the other searches a RAG database. There is no overlap in functionality or ambiguity about when to use each tool.
Both tools use snake_case naming, which is consistent. However, the verb patterns differ slightly: 'read' vs. 'search', which is acceptable but not perfectly uniform. The naming is clear and follows a logical convention.
With only two tools, the server feels severely under-scoped for a RAG (Retrieval-Augmented Generation) system. A typical RAG server would include tools for indexing, updating, deleting, or managing the database, not just reading files and searching. This minimal set limits functionality significantly.
The tool surface is highly incomplete for a RAG domain. There are no tools for indexing documents, updating the database, deleting entries, or managing the RAG system's lifecycle. This forces agents into dead ends for basic operations like adding new data or maintaining the database.