No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by infinitimeless · MCP Server · ★ 168
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LMStudio-MCP A Model Control Protocol (MCP) server that allows Claude to communicate with locally running LLM models via LM Studio. Overview LMStudio-MCP creates a bridge between Claude (with MCP capabilities) and your locally running LM Studio instance. This allows Claude to: Check the health of your LM Studio API List available models Get the currently loaded model Generate chat and raw text completions using your local models Generate vector embeddings for semantic search and RAG Hold stateful multi-turn conversations via response IDs Start and continue persistent conversations with a locked-in system prompt This enables you to leverage your own locally running models through Claude's interface, combining Claude's capabilities with your private models. Prerequisites Python 3.7+ LM Studio installed and running locally with a model loaded Claude with MCP access Required Python packages (see Installation) 🚀 Quick Installation One-Line Install (Recommended) Manual Installation Methods Local Python Installation
| Stars | 168 |
| Forks | 33 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 73.9493503611254/100 |
| Last Updated | 2026-04-10 |
| Created | 2025-03-22 |
| Platforms | claude-code, docker, mcp, python |
| Est. Tokens | ~6k |
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LMStudio-MCP is A Model Control Protocol (MCP) server that allows Claude to communicate with locally running LLM models via LM Studio.. It is categorized as a MCP Server with 168 GitHub stars.
LMStudio-MCP is primarily written in Python.
You can find installation instructions and usage details in the LMStudio-MCP GitHub repository at github.com/infinitimeless/LMStudio-MCP. The project has 168 stars and 33 forks, indicating an active community.
LMStudio-MCP is released under the MIT license, making it free to use and modify according to the license terms.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
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