Multi-Provider MCP Server
Integrates with the OpenAI API to send prompts to models and retrieve responses, enabling side-by-side comparison with other LLM providers.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Multi-Provider MCP ServerCompare Claude, OpenAI, and Gemini on the best way to learn Python."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Multi-Provider MCP Server
A Model Context Protocol server, built on the official Python SDK, whose headline tool asks the same question to Claude, OpenAI, and Gemini and returns the answers side by side. The provider layer is a small adapter interface, so adding a fourth vendor means adding one file.
Tools
Tool | What it does |
| Sends one prompt to every configured provider concurrently and returns each answer keyed by provider. A provider that fails reports its error without hiding the others. |
| Lists the providers that have an API key configured. |
| Fetches a page and returns its title, word count, and a short excerpt. |
| Returns the current time in any IANA timezone. |
Related MCP server: multi-ai-collab
Design
Adapter per vendor.
LLMProviderdefines a singlecomplete(prompt)method.ClaudeProvider,OpenAIProvider, andGeminiProvidereach translate that into their vendor's request and response shape.Providers are opt-in.
build_configured_providersregisters only the vendors whose API key is present in the environment. With no keys set, the comparison tool explains what to configure instead of failing.Logic lives outside the MCP layer. Each tool is a thin wrapper over a plain function, so the behavior is tested directly and again through a real MCP client session.
Injectable dependencies.
create_serveraccepts an HTTP client and a provider factory, which is what lets the test suite run without network access or API keys.
Running it
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
export ANTHROPIC_API_KEY=... # set any combination of the three keys
python -m server.mainThe server speaks MCP over stdio. To use it from an MCP client such as Claude Desktop, register it as a stdio server:
{
"mcpServers": {
"multi-llm": {
"command": "python",
"args": ["-m", "server.main"],
"cwd": "/path/to/mcp-multi-llm-server",
"env": { "ANTHROPIC_API_KEY": "...", "OPENAI_API_KEY": "..." }
}
}
}Default models can be overridden with ANTHROPIC_MODEL, OPENAI_MODEL, and GEMINI_MODEL; see .env.example.
Tests
pip install -r requirements-dev.txt
pytestThe suite mocks the HTTP layer, so it needs no network access and no API keys. It covers each adapter's request and response shape, failure isolation in the comparison, and a full client-to-server round trip over the MCP protocol.
Note that the adapters are verified against mocked responses that follow each vendor's documented API, not against the live services.
License
MIT — see LICENSE.
This server cannot be deployed
Maintenance
Related MCP Connectors
Remote streamable-HTTP MCP server running on a single Cloudflare Worker. Your assistant gets live Airbnb, Amazon, Booking.com, Google Flights, Maps and Reddit data, social search on X, Instagram and TikTok, the Meta Ad Library, and image/video generation without any keys. Connect your own accounts to let it send WhatsApp or Telegram messages, work an IMAP inbox, manage Meta Ads campaigns and publish to X and LinkedIn. OAuth 2.1 with PKCE; stored credentials are AES-256-GCM encrypted.
Shared memory for AI tools: save once, recall word for word from Claude, ChatGPT, Codex or Gemini.
Test and compare prompts across any AI provider. Bring your own keys.
Share context and questions between Claude instances — VS Code, claude.ai web, and mobile.
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