"ollama" matching MCP servers:

Hardened MCP bridge to the full Ollama ecosystem — local and cloud models. 6 tools covering health, model management, chat, and generation with SSRF mitigation, singleton HTTP client, and structured error handling. Two deps, one file.

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.

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.

Integrates Ollama's local AI models with MCP clients, enabling listing models, viewing model details, and asking questions to 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 Claude Code to hand off mechanical work — file edits, code lookups, and lint triage — to a local Ollama model that reads and edits files directly, so file contents never enter Claude's context. Returns only a compact receipt, and reports success only after the change passes a deterministic syntax/project gate, rolling back and escalating on failure.

Enables web search and web fetch operations using Ollama's hosted APIs, allowing MCP clients to search the web and retrieve page content.

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.

A minimal local vision bridge for text-only VS Code Copilot, enabling it to see images by sending them to a local Ollama vision model and returning text descriptions. It provides MCP tools for image description, listing, OCR, and status checks.

Exposes a local Ollama fleet as MCP tools for Claude Code, enabling model listing, generation, fleet health checks, parallel comparisons, smart host routing, and model pulling across hosts.

A Python MCP server that gives vision capabilities to text-only LLMs by exposing an analyze_image tool that sends local images to a vision-capable Ollama model and returns textual descriptions.

Gives AI agents a persistent vector memory by embedding text with Ollama and storing it in Qdrant, so they can save, batch-save, semantically search with payload filters, and delete memories across collections.

Enables performing web searches and fetching web page content via Ollama's hosted APIs, providing search results and raw page data.

MCP server enabling LLM clients without vision capability to process images by delegating to local Ollama vision models. Supports describing images, OCR, asking questions, and processing clipboard images.

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

Enables Google Antigravity CLI to offload token-heavy workloads to local Ollama models through MCP tools for code drafting, summarization, chunked map-reduce, and JSON extraction, reducing cloud token usage.

Enables AI assistants to perform semantic search and retrieval across codebases stored in Qdrant, using Ollama models for GPU-accelerated embeddings.

Enables complete local Ollama management including listing models, chatting with local LLMs, starting/stopping the server, and getting intelligent model recommendations for specific tasks through natural language commands.

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.