"ollama" matching MCP servers:

Enables Claude Code to leverage local Ollama models for tasks like summarizing large files, reviewing diffs, semantic code search, and generating boilerplate or tests, while also supporting a fully offline mode.

Offloads cheap work from cloud LLM agents to a local Ollama model, reducing costs and keeping frontier models focused on complex tasks.

Delegates tasks from an Anthropic-backed Claude Code session to Ollama-backed Claude Code sessions, allowing them to run side-by-side without sharing environment variables.

MCP server for delegating coding tasks to local Ollama models. Supports listing models and executing tasks with file writing capabilities.

MCP server wrapping local Ollama models for offload from API-priced orchestrators. Nine stdio tools - generation, summarisation, analysis, drafting, code tasks (docstring/test/explain/review/types/refactor-suggest), diff-driven tasks (commit-message/pr-description/changelog/summary/impact), mechanical transforms, and model management (list/pull). Apache-2.0.

A VRAM-aware MCP server that offloads token-heavy development tasks to local Ollama models, saving API tokens for complex reasoning.

MCP server that lets Claude Code offload simple tasks like code explanation, writing tests, and adding comments to a local Ollama model, saving Claude API tokens.

Enables natural language queries to PostgreSQL through an Ollama-powered agent, using MCP protocol to connect the backend to the database and a web interface.

Integrates Ollama's local AI models with MCP clients, enabling listing models, viewing model details, and asking questions to models.

Enables locally running an Ollama-powered MCP server to chat with a tool-capable model, retrieve bundled demo documents, and execute /security+ or /format commands through MCP, an authenticated HTTP API, or an interactive CLI.

Lets Claude query and manage a local Ollama server — list models, inspect them, run generate/chat completions, pull or delete models.

MCP Ollama server integrates Ollama models with MCP clients, allowing users to list models, get detailed information, and interact with them through questions.

Enables AI agents to interact with local Ollama models for text generation and tool calling with prompt injection protection.

A universal MCP server that integrates with local Ollama instances, enabling AI-powered chat, model management, and text generation from any MCP-compatible IDE or application.

A comprehensive MCP proxy server that bridges MCP clients with Ollama local language models, providing advanced features like RAG integration, context management, caching, and production-ready security.

A Python MCP server that exposes local Ollama models as tools for AI assistants, enabling chat, generation, embeddings, and model management without cloud APIs.

Enables interaction with locally running Ollama models through chat, generation, and model management operations. Supports listing, downloading, and deleting models while maintaining conversation history for interactive sessions.

A local MCP server that gives Ollama language models sandboxed file management tools—read, write, list, and recoverable delete—within configurable workspace directories, keeping everything local and secure.

Enables text-only AI models to analyze images via local Ollama multimodal models. Supports image analysis, OCR, and multi-image comparison entirely offline.

A server that enables seamless integration between local Ollama LLM instances and MCP-compatible applications, providing advanced task decomposition, evaluation, and workflow management capabilities.