MCP Chat
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| USE_UV | Yes | Set to 1 to use uv, 0 otherwise | |
| LOCAL_LLM_MODEL | Yes | The model name to use with the local LLM (e.g., llama3.2) | |
| LOCAL_LLM_BASE_URL | Yes | The base URL of the local LLM server (e.g., http://localhost:11434/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": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| read_doc_contentsA | Read the contents of a document and return it as a string. |
| edit_documentA | Edit a document by replacing a string in the documents content with a new string |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| format | Rewrites the contents of the document in Markdown format. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| list_docs |
TDQS
Scored across 2 tools
The two tools have distinct purposes: one for editing documents by replacing strings, and another for reading document contents. There is no overlap or ambiguity between them.
Both tool names follow a consistent verb_noun pattern (edit_document, read_doc_contents) using snake_case, making them predictable and easy to understand.
With only two tools, the server feels minimal for general document management, but it may be sufficient for a very narrow chat context. However, the small count is borderline and could benefit from additional operations.
The server lacks create and delete operations for documents, which are essential for a complete CRUD lifecycle. Agents would be unable to add or remove documents, leading to failures in typical workflows.