"ollama" matching MCP servers:

An MCP server that lets Claude Code delegate coding tasks such as code generation, review, refactoring, and test writing to a local Ollama instance running a Qwen3 model.

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.

Bridges Claude with a local Ollama coding model, letting Claude delegate bounded implementation tasks to the local model while retaining reasoning, review, and safety enforcement.

Enables AI-powered code editing with preview and validation capabilities through FastApply language models. Features automatic backups, atomic file operations, and support for multiple FastApply-compatible backends like LM Studio and Ollama.

Enforces a git-tracked, code-checked finite state machine that hands control between a planning director and a local Ollama implementor, exposing tools to check phase status, transition states, and run the implementor to execute plan step files one at a time. It enables a project to be planned, implemented step by step with per-step test gating, and validated before completion.

Classifies software implementation tasks using local Ollama models and recommends coding-agent models based on a deterministic policy.

Enables a fully local multi-agent AI system with 45 specialized agents and 50 predefined workflows via MCP, powered by Ollama and requiring no internet.

Generates project features (HTML pages, backend APIs) from prompts and project-specific business rules stored as resources, with support for interchangeable LLM providers (local Ollama or cloud Gemini).

An MCP server that provides an AI LLM orchestrator supporting multiple providers (LM Studio, Ollama, OpenAI, generic) plus SQLite-backed memory, kanban, and todo databases for persistent task and knowledge management.

MCP server that enables cloud models (like Gemini/Claude) to delegate coding tasks to a local llama.cpp server, preserving cloud usage limits through an AI-powered code review loop.