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72,099 servers. Updated

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"Ollama" matching MCP servers:

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    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.
    6
    3
    MIT
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    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.
    11
    Apache 2.0
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    A VRAM-aware MCP server that offloads token-heavy development tasks to local Ollama models, saving API tokens for complex reasoning.
    840
    MIT
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    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.
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    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.
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    MCP Ollama server integrates Ollama models with MCP clients, allowing users to list models, get detailed information, and interact with them through questions.
    3
    33
    MIT
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    Enables web search and web fetch operations using Ollama's hosted APIs, allowing MCP clients to search the web and retrieve page content.
    2
    MIT
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    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.
    4
    1
    MIT
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    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.
    6
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    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.
    1
    MIT
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    Enables seamless integration between Ollama's local LLM models and MCP-compatible applications, supporting model management and chat interactions.
    13
    840
    170
    AGPL 3.0
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    Enables performing web searches and fetching web page content via Ollama's hosted APIs, providing search results and raw page data.
    2
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    MIT
  • F
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    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.
    4