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Alternatives to llm-mcp

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    Related Servers

    • A
      license
      Not graded
      quality
      D
      maintenance
      Exposes local Ollama instances as tools for Claude Code, allowing users to offload code generation, text drafting, and embedding tasks to local GPUs. It supports multi-turn conversations and model management through the Model Context Protocol.
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    • A
      license
      Not graded
      quality
      D
      maintenance
      A bridge that enables Claude Code to interact with local Ollama instances for text generation, multi-turn chat, and vision-based analysis. It supports model management tasks such as listing, pulling, and showing details, alongside generating text embeddings.
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      MIT
    • A
      license
      B
      quality
      C
      maintenance
      Enables Claude Code to call local generative AI services on a LAN, letting users list and chat with Ollama models and list checkpoints, LoRAs, and samplers or generate and save images via Stable Diffusion WebUI Forge Neo. Requests can be made in natural language, with per-call options for model, image size, and Hires.fix settings.
      1
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Bridges LM Studio local models to Claude Code as MCP tools, enabling private and free AI-assisted subtasks. Includes respond and models tools with automatic model selection and structured output.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables voice assistants to start, monitor, message, and approve local Claude Code sessions on your computer, including sessions already open in a terminal. It exposes session management, recaps, approvals, and history search as MCP tools.
      2
      GPL 3.0

    TDQS

    A3.9/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools occupy entirely disjoint roles: list_models is a read-only discovery/inventory call, while ask performs inference. An agent can unambiguously pick between them, and all the optional knobs (system, model, think, max_tokens) are correctly folded into ask as parameters rather than separate tools.

    Naming Consistency4/5

    list_models follows a clean verb_noun pattern, but ask is a bare verb with no noun, so the set is not fully uniform (ask_model or prompt_model would have matched). With only two tools this is a minor, still-readable deviation.

    Tool Count3/5

    Two tools is thin for a server whose apparent scope is managing and using local models. The surface is defensible because most capability is expressed as ask parameters, but it sits at the borderline of feeling under-specified.

    Completeness3/5

    Discover models and send a single prompt covers the core inference loop, but there is no model lifecycle control (starting/stopping a model, despite list_models reporting start commands and running state), no multi-turn chat, no streaming, and no embeddings. These are notable gaps an agent will hit quickly.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues