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[MOVED → codeberg.org/scarrow/mcp-servers-lmstudio] Concurrent MCP bridge for LM Studio with async multi-agent query support

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[MOVED → codeberg.org/scarrow/mcp-servers-lmstudio] Concurrent MCP bridge for LM Studio with async multi-agent query support

README

One-click installers for Model Context Protocol (MCP) servers that enable LM Studio models to collaborate, query each other, and work together through async operations.

🎯 Quick Install

Click any button below to install MCP servers directly into LM Studio:

Production Servers

Server Description Install Docs
Concurrent Multi-Agent Query multiple models simultaneously with connection pooling 🚀 Install 📖 Docs
Code Reviewer Automated code review using 30B+ models 🚀 Install 📖 Docs
Oracle Database Connect LM Studio to Oracle databases 🚀 Install 📖 Docs
MongoDB MongoDB operations from LM Studio 🚀 Install 📖 Docs

Experimental Servers

Server Description Install Status
Agent Orchestrator Coordinate multiple specialized agents 🧪 Install Beta
VRAM Manager Auto-manage model loading within VRAM limits 🧪 Install Alpha

💡 What is MCP?

Model Context Protocol (MCP) allows LM Studio models to:

  • 🔄 Query other models - One model can ask another for help
  • 🚀 Run concurrently - Multiple models working in parallel
  • 🛠️ Use tools - Connect to databases, APIs, and services
  • 🤖 Self-referential AI - Models can improve their own responses

📊 Model Requirements

Based on extensive testing, here are the minimum model requirements for effective tool use:

Task Complexity Minimum Model VRAM Use Cases
Simple qwen2.5-coder-14b 8.5GB Basic function calls, single tools
Medium codestral-22b 13.5GB Multi-step workflows, sequential logic
Complex qwen3-coder-30b 18GB Nested workflows, dynamic selection
Expert qwen3-32b 19.5GB Error handling, production systems

🔧 Installation Methods

Method 1: One-Click Web Installer (Recommended)

  1. Click any install button above
  2. Your browser will open the installer page
  3. Click "Install in LM Studio"
  4. LM Studio will prompt to add the server

Method 2: Direct Deeplink

Copy and paste these links into your browser:

# Concurrent Multi-Agent Server
lmstudio://add_mcp?name=lmstudio-concurrent&config=eyJjb21tYW5kIjoicHl0aG9uMyIsImFyZ3MiOlsiL3BhdGgvdG8vbG1zdHVkaW9fYnJpZGdlLnB5Il0sImVudiI6eyJMTVNUVURJT19BUElfQkFTRSI6Imh0dHA6Ly9sb2NhbGhvc3Q6MTIzNC92MSJ9fQ==

Method 3: Manual Configuration

Add to ~/.lmstudio/mcp.json:

{
  "mcpServers": {
    "lmstudio-concurrent": {
      "command": "python3",
      "args": ["/path/to/lmstudio_bridge.py"],
      "env": {
        "LMSTUDIO_API_BASE": "http://localhost:1234/v1"
      }
    }
  }
}

Method 4: CLI Installation

# Using the installer generator
python3 generate_installer.py --preset concurrent --open

# Or directly with LM Studio CLI
lmstudio mcp add-json 'lmstudio-concurrent' '{"command":"python3","args":["/path/to/server.py"]}'

🎨 Create Your Own MCP Server

Quick Start Template

# my_mcp_server.py
from mcp import server
import asyncio

@server.tool()
async def my_tool(param: str) -> str:
    """Your tool description"""
    return f"Processed: {param}"

if __name__ == "__main__":
    server.run()

Generate Installer

# Clone this repo
git clone https://github.com/samscarrow/mcp-servers-lmstudio.git
cd mcp-servers-lmstudio

# Generate installer for your server
python3 scripts/generate_installer.py \
  --name "my-server" \
  --script "/path/to/my_mcp_server.py" \
  --output installers/my-server.html \
  --open

📈 Performance Benchmarks

Configuration Response Time Throughput VRAM Usage
Single 14B Model 2.3s 26 tokens/s 8.5GB
2x 14B Concurrent 2.4s 52 tokens/s 17GB
4x 14B Concurrent 2.8s 95 tokens/s 33GB*
1x 30B Model 4.1s 18 tokens/s 18GB

*Using JIT loading with auto-unload

🛡️ Security

⚠️ Important: MCP servers can execute code on your system. Only install servers from trusted sources.

Each installer shows:

  • Full configuration before installation
  • File paths and permissions required
  • Environment variables used
  • Network endpoints accessed

🤝 Contributing

We welcome contributions! To add your MCP server:

  1. Fork this repository
  2. Add your server to installers/
  3. Create documentation in docs/
  4. Submit a pull request

Server Requirements

  • Async/await support for concurrent operations
  • Proper error handling
  • Documentation with examples
  • Security considerations documented
  • Tested with LM Studio v0.3.0+

📚 Resources

📜 License

MIT License - See LICENSE file for details.

🙏 Acknowledgments

  • LM Studio team for the amazing local LLM platform
  • Anthropic for the Model Context Protocol specification
  • Contributors who've shared their MCP servers

Made with ❤️ by the LM Studio community

Last updated: 2025-01-30

from github.com/git-scarrow/mcp-servers-lmstudio

Installing S Lmstudio

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/git-scarrow/mcp-servers-lmstudio

FAQ

Is S Lmstudio MCP free?

Yes, S Lmstudio MCP is free — one-click install via Unyly at no cost.

Does S Lmstudio need an API key?

No, S Lmstudio runs without API keys or environment variables.

Is S Lmstudio hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install S Lmstudio in Claude Desktop, Claude Code or Cursor?

Open S Lmstudio on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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