llm-mcp
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- AlicenseNot gradedqualityDmaintenanceExposes 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.MIT
- AlicenseAqualityBmaintenanceLets Claude query and manage a local Ollama server — list models, inspect them, run generate/chat completions, pull or delete models.8MIT
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- AlicenseNot gradedqualityBmaintenanceBridges 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
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TDQS
Scored across 2 tools
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.
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.
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.
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.