grounded-rag-mcp
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": true
} |
| prompts | {
"listChanged": true
} |
| resources | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| ingest_documentsB | Ingest documents into a named collection so they can be searched. Provide |
| searchA | Search a collection and return the most relevant chunks, each with its source and per-stage scores. mode: hybrid (default) | dense | bm25. Empty result = not in the docs. |
| answerA | Answer a question grounded in a collection, with citations. Retrieves relevant passages and asks the host's model (via MCP sampling) to answer using only those, citing them. Refuses (grounded=false) when nothing relevant is found. |
| list_collectionsA | List all ingested collections and how many chunks each contains. |
| evaluate_retrievalA | Measure retrieval quality on labeled cases: hitRate, mrr, recallAtK. Each case is {query, relevantSources}. Use it to quantify quality and catch regressions. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| grounded_answer | Instructs strict, cited, grounded answering. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| collections | Ingested collections and chunk counts |