OmniLLM: Seamless Multi-LLM Integration & Enterprise Insights

OmniLLM empowers Claude to seamlessly integrate responses from ChatGPT, Azure OpenAI, Gemini & more, building a unified AI knowledge hub for enterprise-scale insights." )

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About OmniLLM

What is OmniLLM: Seamless Multi-LLM Integration & Enterprise Insights?

OmniLLM is an advanced Multi-Cloud Proxy (MCP) server designed to seamlessly integrate responses from multiple large language models (LLMs), including Claude, ChatGPT, Azure OpenAI, and Google Gemini. It acts as a unified gateway for enterprise users, enabling direct queries across different LLM ecosystems while maintaining a single access point. This allows teams to compare outputs, validate results, and optimize workflows by leveraging the unique strengths of each model.

Key Features of OmniLLM: Seamless Multi-LLM Integration & Enterprise Insights?

Cross-Platform Querying: Access OpenAI, Azure OpenAI, and Google Gemini models through a single interface.
Side-by-Side Comparisons: Automatically gather responses from all configured LLMs for direct analysis.
Dynamic Configuration: Activate or disable specific LLM services via API keys in the .env file without code changes.
Enterprise-Grade Control: Monitor active models and troubleshoot connectivity via built-in diagnostics tools.

OmniLLM Features

How to use OmniLLM: Seamless Multi-LLM Integration & Enterprise Insights?

Installation requires three core steps:

Clone the repository and configure API keys in the environment file.
Launch the MCP server using Python's uvicorn or a production-ready web server.
Integrate with existing workflows via REST API endpoints or direct CLI interaction.

For example, querying ChatGPT and Azure simultaneously involves a single API call, with results aggregated in JSON format.

Use Cases for OmniLLM: Seamless Multi-LLM Integration & Enterprise Insights

Organizations use this tool to:

Validate model outputs across providers for compliance or accuracy checks.
Automate A/B testing of LLM performance in specific business scenarios.
Build hybrid models that combine strengths of multiple systems (e.g., GPT-4's reasoning + Gemini's vision capabilities).
Reduce vendor lock-in risks by maintaining multi-cloud LLM access.

OmniLLM FAQ

Frequently Asked Questions

Q: How do I resolve authentication errors?
Verify API keys in your .env file and ensure IAM roles allow cross-cloud access if using Azure or Google services.

Q: Can I customize response weighting?
Yes – adjust the 'model_priority' parameter in config.yaml to influence which model's output is emphasized in aggregated results.

Full documentation includes troubleshooting guides and enterprise deployment best practices.

Content

OmniLLM: Universal LLM Bridge for Claude

OmniLLM is an MCP server that allows Claude to query and integrate responses from other large language models (LLMs) like ChatGPT, Azure OpenAI, and Google Gemini, creating a unified access point for all your AI needs.

Features

Query OpenAI's ChatGPT models
Query Azure OpenAI services
Query Google's Gemini models
Get responses from all LLMs for comparison
Check which LLM services are configured and available

Setup Instructions

1. Prerequisites

Python 3.10+
Claude Desktop application
API keys for the LLMs you want to use

2. Installation

# Clone or download this repository
git clone https://github.com/yourusername/omnillm-mcp.git
cd omnillm-mcp

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install mcp[cli] httpx python-dotenv

3. Configuration

Create a .env file in the project root with your API keys:

OPENAI_API_KEY=your_openai_key_here
AZURE_OPENAI_API_KEY=your_azure_key_here
AZURE_OPENAI_ENDPOINT=your_azure_endpoint_here
GOOGLE_API_KEY=your_google_api_key_here

You only need to add the keys for the services you want to use.

4. Integrating with Claude Desktop

Open Claude Desktop
Navigate to Settings > Developer > Edit Config
Add the server to your claude_desktop_config.json file:

{
  "mcpServers": {
    "omnillm": {
      "command": "python",
      "args": [
        "path/to/server.py"
      ],
      "env": {
        "PYTHONPATH": "path/to/omnillm-mcp"
      }
    }
  }
}

Replace "path/to/server.py" with the actual path to your server.py file.

Save the config file and restart Claude Desktop

Usage Examples

Once connected to Claude Desktop, you can use phrases like:

"What would be the top places to visit if you're looking for an adventurous hiking trip? Consult ChatGPT"
"What's the best way to learn programming? Ask Gemini for their opinion."
"Compare different frameworks for building web applications, and then get input from both ChatGPT and Azure OpenAI"

Claude will automatically detect when to use the Multi-LLM Proxy tools to enhance its responses.

Available Tools

query_chatgpt - Query OpenAI's ChatGPT with a custom prompt
query_azure_chatgpt - Query Azure OpenAI's ChatGPT with a custom prompt
query_gemini - Query Google's Gemini with a custom prompt
query_all_llms - Query all available LLMs and get all responses together
check_available_models - Check which LLM APIs are properly configured

Troubleshooting

Check that your API keys are correctly set in the .env file
Ensure Claude Desktop is properly configured with the server path
Verify that all dependencies are installed in your virtual environment
Check Claude's logs for any connection or execution errors

License

MIT License