local-llm-delegation-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
} |
| 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 |
|---|---|
| query_local_llmB | Query the local LLM for simple, well-defined subtasks that have already been broken down. IMPORTANT: Always try this tool FIRST for any simple code generation to save costs! |
| query_local_llm_with_contextB | Query the local LLM for simple subtasks that require additional context. Use this for code reviews, documentation, or refactoring. |
| get_local_llm_usage_statsA | Retrieve and summarize usage statistics for the local LLM MCP server. |
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
get_local_llm_usage_stats is clearly distinct (usage statistics). query_local_llm and query_local_llm_with_context both query the model, but the descriptions clearly separate them: one for well-defined subtasks without context, the other for tasks requiring additional context (code reviews, docs, refactoring). The usage guidance further reduces ambiguity.
All tool names follow a consistent verb_noun pattern in snake_case: get_local_llm_usage_stats, query_local_llm, query_local_llm_with_context. The prefix is always a verb (get/query) and the resource is specific, making the naming predictable and uniform.
With 3 tools, the server is on the lower end of the typical range but not thin. The tools cover the core actions for local LLM delegation: querying (with and without context) and retrieving usage stats. It could benefit from a couple more (e.g., listing models or canceling a query), but it feels reasonably scoped for its purpose.
The tool set covers the main workflows of local LLM delegation: basic queries and context-augmented queries, plus usage monitoring. Minor gaps include lack of model list or query cancellation, but these are not critical for the stated purpose of handling simple, well-defined subtasks. The surface is adequate and workable.