LM Studio MCP Server
Related Servers
Alternatives to LM Studio MCP Server
No user-submitted related servers found.
Related Servers
- AlicenseAqualityDmaintenanceEnables listing, loading, unloading, and configuring models in LM Studio via MCP tools, with support for TTL and draft model settings.56MIT
- AlicenseNot gradedqualityAmaintenanceEnables 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.621 npmMIT
- AlicenseNot gradedqualityCmaintenanceExposes local LM Studio language models as MCP tools, enabling chat completions and model listing through a local OpenAI-compatible API without requiring API keys.MIT
- AlicenseNot gradedqualityDmaintenanceEnables 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.358 npmMIT
- FlicenseCqualityDmaintenanceEnables MCP clients to interact with local LLMs via LM Studio, supporting dynamic chat, vision, RAG, file interaction, and model orchestration.28-
- AlicenseNot gradedqualityDmaintenanceProvides AI assistants with structured access to metadata for 76+ AI models across Ollama, Claude, and OpenRouter, enabling capability queries, compatibility checks, model comparisons, and task-based recommendations.8 npmMIT
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose: health_check for connectivity, list_models vs list_loaded_models for different sets, get_model_info for details on a loaded model, and load/unload for lifecycle management. No ambiguity.
Most tools follow a verb_noun pattern (get_model_info, list_choices, load_model, unload_model). health_check deviates as a noun phrase but is conventional and understandable. Overall consistent.
With 6 tools covering connectivity, listing, loading/unloading, and info query, the count is well-scoped for the domain of model management without bloat or deficiency.
The set covers core model lifecycle (load, unload, list, info) and connectivity. Minor gaps like model deletion or parameter configuration are not critical for common agent tasks.