"Integrating Claude Desktop with a Local LLM using the LMStudio API" matching MCP servers:

An MCP server that allows Claude to interact with local LLMs running in LM Studio, providing access to list models, generate text, and use chat completions through local models.

Enables asynchronous two-way messaging between Codex Desktop tasks and Claude Desktop Code sessions on Windows, allowing either side to share information, questions, or updates through MCP tools.

Bridges local LLMs running in LM Studio with MCP clients like Claude Desktop to perform reasoning and analysis tasks while keeping sensitive data private. It features a suite of tools for local code review, privacy scanning, and content transformation using auto-discovered local models.

A bidirectional MCP bridge that lets Claude Desktop and Claude Code collaborate on a build with no human in the execution loop.

A server that enables Claude Desktop users to access the Claude API directly, allowing them to bypass Professional Plan limitations and use advanced features like custom system prompts and conversation management.

Enables a local-first autonomous coding agent that plans, edits, and verifies code using LM Studio, Ollama, or llama.cpp models, with hardware-aware parallel sub-agents and optional frontier-model planning.

Enables Claude Code to hand off bulk, mechanical, read-heavy tasks to a local model, including agentic loops that can read, write, and run commands sandboxed at zero cloud token cost.

Blind multi-model councils with anonymous LLM seats and direct 1:1 chat as a local MCP server. Enables asking one question to get independent answers from multiple model CLIs, then blind scoring and reveal.

Enables structured learning with a verified loop: define goals as observable claims, learn through teach-lab-test-gate per claim, and get independently graded by an adversarial examiner to ensure genuine progress.

An MCP server that lets agents observe and control an Omarchy or Hyprland desktop: list monitors, windows, workspaces, and accessibility controls, capture screenshots, then move the pointer, type text, send shortcuts, and manage windows and workspaces. It works over stdio with any MCP client, guarding actions with session-lock and single-driver checks while treating on-screen content as untrusted data.

A compact facade MCP server for macOS desktop automation, lazily proxying to full-featured computer-use tools to save context tokens while enabling screenshots, window control, app launching, and AppleScript execution.

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

Enables supervised, visible control of a Windows desktop from an MCP client, providing real mouse and keyboard input, screenshots, local safety controls, and a teaching mode for guidance without injection.

Enables AI agents to audit generated code locally via LM Studio, using AST checks to catch syntax errors and dangerous calls, and enforcing APPROVED/REJECTED feedback loops for automatic refactoring.

A generic OpenAI-compatible subagent MCP server that lets Claude Code delegate coding grunt-work to a local model via a tool-calling agent loop, with configurable concurrency and backend.

MCP server that provides tools for evaluating LLM agent reliability, including adversarial task generation, automated LLM-as-judge assessment, and confidence statistics.

An MCP server that lets Claude Code consult stronger AI models (o3, Gemini 2.5 Pro, DeepSeek Reasoner) when you need deeper analysis on complex problems.

Windows desktop automation MCP server enabling screenshot capture, precise visual locating of UI elements via vision models, and automated mouse clicking.

Enables multiple local AI desktop applications to exchange MCP messages and collaborate through a shared JSONL room file, with role-based routing, history, and audit session tools.

Enables MCP clients to capture screenshots and control a Raspberry Pi's Wayland desktop over an existing SSH connection with mouse, drag, scroll, keyboard, and Unicode typing actions. Input tools return fresh screenshots, enforce single-client sessions with idle release, and reject stale or uncertain state until verified.

Centralized encrypted gateway that routes requests to 11+ LLM providers (API keys and CLI subscriptions) through a single OpenAI-compatible endpoint, with MCP tools for vault operations, code search, and shared state.

MCP server for The Commons (jointhecommons.space), a persistent, noncommercial space where AI voices from different models post and reply to each other with persistent identities. 48 tools; reading needs no token, writing uses a facilitator-issued token.

MCP server that provides a live coordination layer for AI agents, including attributable handoffs, a shared event ledger, atomic work-claiming, and advisory file leases to prevent collisions.

Enables an LLM assistant to inspect and operate a Factorio 2.1 world through MCP and local RCON, including pathfinding, crafting, building from inventory, blueprint handling, site planning, and train schedule updates via a persistent companion mod.

An MCP server that provides LLMs access to other LLMs

A privacy-first MCP server that provides local LLM-enhanced tools for code analysis, security scanning, and automated task execution using backends like Ollama and LM Studio. It enables symbol-aware code reviews and workspace exploration while ensuring that all code and analysis remain strictly on your local machine.

Enables Claude Code as a team leader to delegate tasks to GPT and Gemini experts, supporting multi-LLM collaboration with tools for consultation, code review, design, and background execution.

Enables a local MCP client to drive an already-open DeepSeek Harness Desktop session over a loopback-only, Bearer-authenticated endpoint — submitting standard-mode tasks, reading bounded output, continuing or canceling runs, and inspecting diagnostics.

Enables other agents to list, read, start, and steer Codex chats in the macOS ChatGPT desktop app, including sending follow-ups, choosing model/reasoning/speed, interrupting work, and answering approvals. It can run locally or behind bearer-token-protected tunnels for remote monitoring and control.

Enables guarded, local-first perception and interaction with Windows desktops through UI Automation, screenshots, and bounded mouse/keyboard actions with deterministic verification. It prioritizes semantic/read-only inspection and excludes arbitrary shell execution or destructive system operations.