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Glama
koyakimu

local-llm-mcp

by koyakimu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
LOCAL_LLM_MODELNoModel name to request from the local server.first model from /v1/models
LOCAL_LLM_API_KEYNoOptional API key sent as Authorization: Bearer ... if set.
LOCAL_LLM_TIMEOUTNoTimeout in seconds; the first call may include model loading.600
LOCAL_LLM_BASE_URLNoOpenAI-compatible base URL of the local LLM server.http://127.0.0.1:8080/v1
LOCAL_LLM_ALLOWED_ROOTSNoColon-separated directories that files may be read from and written to.~, /tmp, $TMPDIR, and the macOS per-user temp dir
LOCAL_LLM_MAX_INPUT_CHARSNoLimit for prompt + files in characters.60000

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

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
local_llmA

Run a task on a local LLM on this machine. Nothing is sent to the cloud.

Use it for (1) private data that must not leave the machine: pass file paths in files instead of reading them yourself; this server reads them and only the local model's answer comes back to you; and (2) bulk, mechanical text work (summarizing, classifying, translating, reformatting) where a smaller model is good enough. Do not use it for tasks that need strong reasoning or careful code changes.

Files must be under the home directory or /tmp and must not be hidden (no path component starting with ".").

Args: prompt: The instruction for the local model. Write it self-contained; the model sees nothing else. files: Text files to include after the prompt (UTF-8). Total input is capped (~60k characters). output_path: If set, the answer is written to this new file and only a short notice is returned, so even the answer stays out of the conversation. Existing files are never overwritten. system: Optional system prompt. max_tokens: Maximum tokens to generate. thinking: Enable the model's thinking mode, if it has one (slower, sometimes more accurate).

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

TDQS

A4.8/5.0

Scored across 1 tool

Disambiguation5/5

There is only one tool, so there is no possibility of confusion or misselection between tools. Its purpose (run a task on a local LLM) is unambiguous and clearly stated.

Naming Consistency4/5

With a single tool named `local_llm`, there is no convention to break, so consistency is trivially satisfied. It uses a clear snake_case noun rather than a verb_noun pattern, which is a minor deviation but perfectly readable.

Tool Count4/5

A single, argument-rich tool is a reasonable fit for a narrowly scoped domain like invoking a local LLM, and nothing obvious is bolted on unnecessarily. It sits at the low end of the typical range, but the domain genuinely appears to need only one entry point.

Completeness4/5

The tool's arguments cover the core lifecycle for its purpose: prompt, context files, output redirection, system prompt, token limit, and thinking mode. Minor gaps exist (e.g. no way to list or select available local models or check readiness), but agents can work around these.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources