LMStudio-MCP
@infinitimeless
About LMStudio-MCP
A Model Control Protocol (MCP) server that allows Claude to communicate with locally running LLM models via LM Studio.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"LMStudio-MCP": {
"command": "python",
"args": [
"lmstudio_bridge.py"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is LMStudio-MCP?
LMStudio-MCP is a Model Context Protocol (MCP) server that bridges Claude with locally running LLM models via LM Studio. It is for developers who want to use private, offline AI models through Claude’s interface.
How to use LMStudio-MCP?
Install LMStudio-MCP via one-line script, manual Python setup, Docker, or Docker Compose. Configure it with environment variables for host/port, then add the appropriate MCP configuration to Claude. Start LM Studio with a loaded model, and Claude will be able to call the server’s tools.
Key features of LMStudio-MCP
- Check LM Studio API health
- List and identify loaded models
- Generate chat and raw text completions
- Create vector embeddings for semantic search
- Maintain stateful multi-turn conversations
- Start persistent sessions with a locked system prompt
Use cases of LMStudio-MCP
- Private/offline inference without sending data to external APIs
- Semantic search and RAG workflows via embeddings
- Multi-turn conversational agents with persistent context
- Local coding assistant with consistent behaviour
- Privacy-first document analysis with accurate summarisation
FAQ from LMStudio-MCP
What are the dependencies for LMStudio-MCP?
Python 3.7+, a running LM Studio instance with a model loaded, MCP-compatible Claude client, and the requests, mcp[cli], and openai Python packages.
Where does LMStudio-MCP process data?
All inference happens locally on your machine via LM Studio; no data is sent to external services.
Are there any version requirements for certain tools?
create_response, start_conversation, and continue_conversation require LM Studio v0.3.29+. generate_embeddings requires an embedding-specific model (e.g., text-embedding-nomic-embed-text-v1.5).
Frequently asked questions
What are the dependencies for LMStudio-MCP?
Python 3.7+, a running LM Studio instance with a model loaded, MCP-compatible Claude client, and the `requests`, `mcp[cli]`, and `openai` Python packages.
Where does LMStudio-MCP process data?
All inference happens locally on your machine via LM Studio; no data is sent to external services.
Are there any version requirements for certain tools?
`create_response`, `start_conversation`, and `continue_conversation` require LM Studio v0.3.29+. `generate_embeddings` requires an embedding-specific model (e.g., `text-embedding-nomic-embed-text-v1.5`).
Basic information
More AI & Agents MCP servers
1Panel
1Panel-dev🔥 1Panel is a modern, open-source VPS control panel — and the only one with native AI agent support. Run Ollama models, deploy OpenClaw agents, and manage your entire server stack from one clean web interface.
21st.dev Magic AI Agent
21st-devIt's like v0 but in your Cursor/WindSurf/Cline. 21st dev Magic MCP server for working with your frontend like Magic
Transform MCP
UnstructuredThe Unstructured Transform MCP Server connects your ADK agent to Unstructured, a document processing platform that turns raw files into structured, AI-ready data. This integration gives your agent the ability to parse PD
Perplexity Ask MCP Server
ppl-aiThe official MCP server implementation for the Perplexity API Platform
Model Context Protocol for Unreal Engine
chongdashuEnable AI assistant clients like Cursor, Windsurf and Claude Desktop to control Unreal Engine through natural language using the Model Context Protocol (MCP).
Comments