rag-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| EMBED_DIM | No | Dimension of the embedding vectors. Must match the model (default: 1536). | |
| CHUNK_SIZE | No | Number of characters per chunk (default: 1000). | |
| DATABASE_URL | Yes | PostgreSQL connection string (e.g., postgresql://postgres:postgres@localhost:5432/rag). Required. | |
| CHUNK_OVERLAP | No | Number of overlapping characters between chunks (default: 200). | |
| MCP_TRANSPORT | No | Transport protocol: 'stdio' or 'http' (default: stdio). | |
| EMBEDDINGS_MODEL | No | Embedding model name (default: text-embedding-3-small). | |
| EMBEDDINGS_API_KEY | Yes | API key for the embeddings endpoint (OpenAI-compatible). Required. | |
| EMBEDDINGS_API_BASE | No | Base URL for the embeddings API (default: https://api.openai.com/v1). |
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
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| ingest_textA | Chunk, embed, and store text in a collection for later semantic search. collection: logical namespace (e.g. a project or document set). metadata: optional JSON attached to every chunk (source, title, url, ...). |
| searchA | Semantic search a collection. Returns the top-k chunks with a 0-1 cosine score. |
| list_collectionsA | List all collections and their chunk counts. |
| delete_collectionA | Delete a collection and all of its chunks. Irreversible. |
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 distinct purpose: delete_collection removes a collection, ingest_text adds content, list_collections enumerates collections, and search queries them. There is no functional overlap.
All tool names follow a consistent verb_noun snake_case pattern (e.g., delete_collection, ingest_text, list_collections). Even 'search' fits as a verb describing the action.
With 4 tools, the server provides essential RAG operations (CRUD for collections plus search) without being too sparse or overly complex. This is appropriate for its purpose.
The tool surface covers the core workflow: list collections, ingest text, search, and delete. Missing update or get collection details, but these represent minor gaps that agents can work around.