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LM Studio MCP Bridge

by ozwei
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Alternatives to LM Studio MCP Bridge

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    Related Servers

    • llmstudio-mcp

      dam2452
      F
      license
      A
      quality
      D
      maintenance
      MCP server that connects LLM agents to a local LM Studio instance, enabling model management, OpenAI-compatible chat completions, text completions, and embeddings through a set of tools.
      9
      1
      -

    • Ollama MCP Server

      rawveg
      A
      license
      A
      quality
      D
      maintenance
      Enables seamless integration between Ollama's local LLM models and MCP-compatible applications, supporting model management and chat interactions.
      13
      1,210 npm
      173
      AGPL 3.0

    • lmstudio-local

      didou92i
      F
      license
      B
      quality
      C
      maintenance
      Enables MCP clients to administer a local LM Studio instance: loading, estimating, downloading, configuring and unloading models, running chat and embedding inference, diagnosing the server, engines and hardware, and managing MCP connectors with conflict-safe configuration. It also builds a local document index supporting citation-checked search and answers grounded in TXT, Markdown, PDF and DOCX files.
      28
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    • subforge-mcp

      nathan-vm
      A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI clients to interact with models running locally in LM Studio, including listing loaded models, chatting with per-session history, and loading models into memory with user consent.
      40 npm
      MIT
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    C2.4/5.0

    Scored across 28 tools

    Disambiguation2/5

    Multiple tools have overlapping purposes: get_system_health, check_server_status, and lms_status all report health status; list_local_models, lms_ls, and lms_ps all list models in different forms. The distinction between query_local_llm and query_local_llm_stateful is clear but other boundaries (e.g., lms_server_control vs lms_runtime_control) are fuzzy.

    Naming Consistency2/5

    Naming conventions are mixed: most tools use snake_case (get_system_health, query_local_llm), but a subset uses an lms_ prefix (lms_status, lms_ps, lms_get). Verb choices vary inconsistently across similar actions (list vs get vs check vs read), and the async variant `analyze_local_image_async` does not follow a systematic pattern.

    Tool Count2/5

    With 28 tools, the set is bloated. Many tools duplicate functionality or could be consolidated (e.g., multiple health check tools, multiple model listing tools). A more streamlined set of around 15-18 core tools would better align with the bridge's purpose.

    Completeness3/5

    The tool surface covers core workflows: model lifecycle, inference, vision, RAG, embeddings, file access, and network mesh. However, there are notable gaps such as no explicit tool to delete/unload models (only load/unload by model instance) and no way to cancel or manage background tasks beyond checking status. The redundancy in health/status commands also creates confusion but not missing functionality.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources