"Using llama.cpp and Searxng with local models" matching MCP servers:

Enables local llama.cpp inference and dotbot agent workflows through MCP, providing one-shot chat completions and agentic tool loops.

Enables two local LLMs (Qwen and Llama) to communicate via MCP, allowing one model to consult the other for second opinions or additional reasoning.

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.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Provides a local MCP bridge for AI assistants to control a Mac by observing screen state and performing actions like mouse movement, clicking, typing, and opening URLs.

Enables any MCP client to delegate a scoped task to a local Ollama model that runs its own tool-calling loop for file operations and web search, with an allow-listed folder security model.

A local-first MCP memory server that gives AI coding agents persistent memory with hybrid semantic and keyword retrieval, working fully offline.

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.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

Enables compatible AI apps to observe and control a locally connected iPhone through stdio MCP tools for screenshots, taps, swipes, long presses, text entry, key and button presses, app listing, and app launching, all reusing the console's device session.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

Enables ChatGPT or other MCP clients to control native Codex sessions on Windows, providing tools for thread management, turns, observation, steering, and responding to approvals.

Enables AI agent hosts to exchange durable, local sender/receiver messages through a SQLite mailbox exposed as MCP tools (connect, send, receive, reply, ack, status, disconnect), so a coordinator can dispatch commands and an executor can return results without model polling while idle. A configured host wake adapter is still required to turn an incoming event into an Agent turn.

A universal MCP server that enables any LLM or AI agent to access expert skills from your local filesystem.

Local-first MCP server for per-agent key management, generating and using signing keys without external KMS.

Enables Codex to delegate coding tasks to a locally hosted Qwen model through an MCP tool, which can read, write, patch, test, and inspect git diffs inside an allowed workspace.

Provides MCP tools to search a cached index of installed agent skills, MCP tools, and plugins, inspect exact results, and activate skills for supported agents.

Enables a cloud coding agent to delegate a focused coding task to a local Ollama or OpenAI-compatible model through a bounded workspace, file allowlist, and required external checks. Changes are applied only after verification against the declared scope, with failed post-apply checks rolled back and the rollback itself confirmed.

Enables Notion AI to interact with local files, execute shell commands, and delegate complex tasks to local AI agents. Provides file operations, command execution, and task delegation capabilities for local workspace management.