RagLit MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OPENAI_API_KEY | Yes | Your OpenAI API key for embedding generation. | |
| EMBEDDING_MODEL | No | The OpenAI embedding model to use. | text-embedding-3-small |
| EXTERNAL_API_KEY | Yes | The API key for PostgREST (if required). | |
| EXTERNAL_API_URL | Yes | The URL of the PostgREST or Supabase instance. |
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
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| chunk_documentD | – |
| search_chunksD | – |
| filter_metadataD | – |
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 3 tools
Each tool targets a distinct step in the RAG pipeline: chunking documents, searching chunks, and filtering by metadata. The purposes are clearly separable based on names alone, with no overlapping actions.
All tool names follow a consistent verb_noun pattern in snake_case: chunk_document, search_chunks, filter_metadata. This creates a predictable and readable naming convention.
Three tools is on the lower end of the well-scoped range (3-15), but it covers the core RAG operations without being sparse. The count is reasonable for a focused server, though slightly minimal.
The tool set covers the essential lifecycle for a simple RAG server: ingest (chunk), retrieve (search), and refine (filter). Minor gaps exist, such as lack of explicit document management or chunk retrieval, but the core workflow is functional.