Multi LLM Cross-Check MCP Server
About
A Model Control Protocol (MCP) server that allows cross-checking responses from multiple LLM providers simultaneously. It integrates with Claude Desktop as an MCP server to provide a unified interface for querying different LLM APIs.
Details
- Author
- MCP-Mirror
- Downloads
- 208
- Categories
- AI
Jump to
- Query multiple LLM providers in parallel
- Supports OpenAI, Anthropic (Claude), Perplexity AI, and Google (Gemini)
- Asynchronous parallel processing for faster responses
- Easy integration with Claude Desktop
- Individual API errors do not affect other providers
- Only configured providers are queried (skips missing API keys)
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Multi LLM Cross-Check MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install Python 3.8+, uv, and the required API keys. Clone the repository, create a uv environment, and install dependencies. Configure the server in Claude Desktop by adding a JSON entry to claude_desktop_config.json with the command uv run main.py and environment variables for each provider's API key. Once configured, start a conversation in Claude Desktop and ask to “cross check with other LLMs” to use the cross_check tool.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"multi llm cross-check mcp server": {
"lior-ps_multi-llm-cross-check-mcp-server": {
"command": "uv",
"args": [
"venv"
]
}
}
}
}
McpServers
{
"lior-ps_multi-llm-cross-check-mcp-server": {
"command": "uv",
"args": [
"venv"
]
}
}
Multi LLM Cross-Check MCP Server
A Model Control Protocol (MCP) server that allows cross-checking responses from multiple LLM providers simultaneously. This server integrates with Claude Desktop as an MCP server to provide a unified interface for querying different LLM APIs.
Features
- Query multiple LLM providers in parallel
- Currently supports:
- OpenAI (ChatGPT)
- Anthropic (Claude)
- Perplexity AI
- Google (Gemini)
- Asynchronous parallel processing for faster responses
- Easy integration with Claude Desktop
Prerequisites
- Python 3.8 or higher
- API keys for the LLM providers you want to use
- uv package manager (install with pip install uv)
Installation
1. Clone this repository:
git clone https://github.com/lior-ps/multi-llm-cross-check-mcp-server.git
cd multi-llm-cross-check-mcp-server
2. Initialize uv environment and install requirements:
uv venv
uv pip install -r requirements.txt
3. Configure in Claude Desktop:
Create a file named claude_desktop_config.json in your Claude Desktop configuration directory with the following content:
{
"mcp_servers": [
{
"command": "uv",
"args": [
"--directory",
"/multi-llm-cross-check-mcp-server",
"run",
"main.py"
],
"env": {
"OPENAI_API_KEY": "your_openai_key", // Get from https://platform.openai.com/api-keys
"ANTHROPIC_API_KEY": "your_anthropic_key", // Get from https://console.anthropic.com/account/keys
"PERPLEXITY_API_KEY": "your_perplexity_key", // Get from https://www.perplexity.ai/settings/api
"GEMINI_API_KEY": "your_gemini_key" // Get from https://makersuite.google.com/app/apikey
}
}
]
}
Notes:
1. You only need to add the API keys for the LLM providers you want to use. The server will skip any providers without configured API keys.
2. You may need to put the full path to the uv executable in the command field. You can get this by running which uv on MacOS/Linux or where uv on Windows.
Using the MCP Server
Once configured:
1. The server will automatically start when you open Claude Desktop
2. You can use the cross_check tool in your conversations by asking to "cross check with other LLMs"
3. Provide a prompt, and it will return responses from all configured LLM providers
API Response Format
The server returns a dictionary with responses from each LLM provider:
{
"ChatGPT": { ... },
"Claude": { ... },
"Perplexity": { ... },
"Gemini": { ... }
}
Error Handling
- If an API key is not provided for a specific LLM, that provider will be skipped
- API errors are caught and returned in the response
- Each LLM's response is independent, so errors with one provider won't affect others
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License - see the LICENSE file for details.
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