Local AI MCP
Unified MCP server for managing local model runtimes (Ollama, LM Studio, and more): provider-agnostic discovery, lifecycle, hardware-fit, and delegated inference.
What it is
An operations-first control plane for the models on your own machine. It discovers, inspects, fits, and manages local runtimes over their local HTTP APIs, exposing one consistent tool surface across them. It runs over stdio only and is a client to your runtimes — it never opens a network listener of its own.
Inference is delegation, not chat
The complete and embed tools delegate (offload) inference to a local model for cost control and privacy — keeping tokens and data on your hardware instead of a hosted API. They are inference primitives, not a conversational chat surface.
Provider-adapter model
Each runtime is an adapter behind a single Provider interface. Every tool takes an optional provider argument; omit it and the tool operates across all detected runtimes.
| Adapter | Default host | Notes |
|---|---|---|
| Ollama | http://localhost:11434 | Native REST + OpenAI-compatible /v1; load/unload via keep_alive. |
| LM Studio | http://localhost:1234 | REST /api/v0 + OpenAI-compatible; lms CLI for load/unload/pull when present. |
Tools (16)
list_providers
Runtimes, host, live status, capabilities.
list_models
Installed models across providers.
list_loaded
Models resident in memory.
model_info
Detailed model metadata.
pull_model heavy
Download a model (multiple GB).
remove_model destructive
Delete a model; requires confirm.
load_model
Load a model into memory.
unload_model
Evict a model from memory.
health_check
Liveness and version per provider.
system_resources
RAM, CPU, and GPU/VRAM.
fit_check
Does a model fit in VRAM or RAM?
benchmark heavy
Latency and tokens/sec.
search_available
Search a curated model catalog.
suggest_model
Recommend by task and hardware fit.
complete
Delegate a completion (offload).
embed
Delegate embedding generation.
Install
npx @tmhs/local-ai-mcpConfigure via OLLAMA_HOST, LMSTUDIO_HOST, LOCAL_AI_REQUEST_TIMEOUT_MS, and LOCAL_AI_DETECT_TIMEOUT_MS.