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Multi LLM Cross-Check MCP Server

Multi LLM Cross-Check MCP Server

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github.com/lior-psAI & Agents15Updated 75w ago

About Multi LLM Cross-Check MCP Server

An MCP server for users of Claude Desktop and other MCP clients to query multiple LLM providers in parallel and compare their responses. Providers without configured API keys are skipped, and one provider’s error does not prevent others from returning results.

Key features

  1. 01Parallel queries to multiple LLM providers
  2. 02Supports OpenAI, Anthropic, Perplexity AI, and Google
  3. 03Asynchronous request processing
  4. 04Separate responses and errors per provider

Use cases

  1. 01Compare several LLM responses to one question
  2. 02Run cross-checks in Claude Desktop conversations

MCP support

Exposes a `cross_check` tool through MCP for clients to submit a prompt and receive responses from configured providers. The README describes integration with Claude Desktop.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"multi-llm-cross-check": {
"command": "npx",
"args": [
"-y",
"@smithery/cli"
]
}
}
}
Run commandnpx -y @smithery/cli

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@smithery/cli

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MseeP.ai Security Assessment Badge

Multi LLM Cross-Check MCP Server

smithery badge 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

Installing via Smithery

To install Multi LLM Cross-Check Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @lior-ps/multi-llm-cross-check-mcp-server --client claude
Manual 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
  1. Initialize uv environment and install requirements:
uv venv
uv pip install -r requirements.txt
  1. 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

Verified on MseeP

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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