Skip to main content
Glama
obyrned

Local MLX MCP

by obyrned
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Hybrid

Local MLX MCP

An MCP server that turns three locally hosted models into named tools inside Claude Desktop and Codex.

The models run on a Mac mini using MLX. The bridge exposes them over the LAN, so a laptop on the same network can call a local model as a tool without installing anything or shipping the prompt to a hosted API.

Tools

Tool

What it does

list_local_models

Lists the models the host is currently serving.

ask_llama

Llama 3.2 3B. Fast, for quick passes.

ask_qwen

Qwen 3.5 4B. Reasoning and code.

ask_gemma

Gemma 4 E2B. General purpose.

Any of the ask_* tools can optionally run a SearXNG search first and pass the results to the model, so a local model can answer questions about things that happened after its training cutoff.

Related MCP server: local-mcp

Why bother

Two reasons, and neither is cost.

The first is data. Some documents cannot go to a hosted API, and "cannot" is a policy fact rather than a preference. Having a local model available as a tool means the sensitive step of a workflow can run locally while the rest of it runs wherever it likes.

The second is that routing is a real design decision. Not every step needs a frontier model. Being able to name a small local model as the worker for a cheap step, in the same interface where the expensive steps run, makes that decision explicit instead of accidental.

Running it

Over HTTP, for LAN clients:

node server/mlx-bridge.mjs
# listens on 0.0.0.0:8090

Over stdio, for a local client:

node server/mlx-bridge.mjs --stdio

Point it at the host serving the models:

MLX_HOST=http://127.0.0.1   # or the host's LAN address
MCP_PORT=8090

The upstream model servers are OpenAI-compatible, so the bridge speaks ordinary chat-completions to them on ports 8000, 8001, and 8002.

Claude Desktop extension

claude-extension/ packages the same server as a desktop extension with a manifest declaring the four tools. Install it and the models appear as tools without editing a config file by hand.

Wiring it into a client config

Copy mcp.json.example, replace the placeholder paths with absolute paths, and drop it into your client's MCP config location. The example also includes the SearXNG server, since the two are normally used together.

Running the models at boot

launchd/ holds the macOS agents that keep the model servers and the bridge running: one per model plus one for the bridge itself. Paths in these files are placeholders and need to be pointed at your install before loading them with launchctl.

Requirements

  • Node 18 or newer.

  • A host serving MLX models on the expected ports.

  • Optional: a SearXNG instance for the search-augmented calls.

Memory is the real constraint. On a 16 GB machine, running three MLX models, an embedding model, and Ollama at once does not work. Pick which ones stay loaded.

Licence

MIT.

This server cannot be installed

A
license - permissive license
-
quality - not tested
C
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Servers

  • local-mcp

    jkjoplin
    A
    license
    -
    quality
    D
    maintenance
    Enables running MCP tools against local MLX models on your Mac, with hardware-aware configuration, CLI streaming, and a dashboard for routing and monitoring.
    5,294
    Inno Setup

  • searxng-mcp-bridge

    designcomputer
    A
    license
    -
    quality
    A
    maintenance
    A minimal MCP server that exposes a private SearXNG instance as a search tool over streamable-HTTP, enabling web search from the llama.cpp WebUI or any compatible MCP client.
    1
    MIT

  • MCP Research Tools

    hippogriff-ai
    A
    license
    -
    quality
    D
    maintenance
    Local-first MCP server that gives Claude Code web search, page reading, video transcription, and image analysis — without paid API keys. Runs SearXNG + whisper.cpp natively on Apple Silicon for zero-cost, low-latency research workflows.
    MIT

View all related MCP servers

Related MCP Connectors

  • hithereiamaliff-mcp-nextcloud

    A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…

  • Kody

    Personal assistant MCP server with search, execute, packages, jobs, secrets, and integrations.

  • saagarpatel.dev Portfolio

    Agent-native MCP server over the public saagarpatel.dev corpus. Read-only, stateless.

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/obyrned/local-mlx-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server