OpenAI MCP Server
@MCP-Mirror
About OpenAI MCP Server
Mirror of
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"openai-server": {
"command": "python",
"args": [
"-m",
"src.mcp_server_openai.server"
],
"env": {
"PYTHONPATH": "C:/path/to/your/mcp-server-openai",
"OPENAI_API_KEY": "your-key-here"
}
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is OpenAI MCP Server?
OpenAI MCP Server is an MCP (Model Context Protocol) server that lets you query OpenAI models directly from Claude. It bridges OpenAI’s API with Claude’s interface, enabling seamless AI model switching within Claude Desktop.
How to use OpenAI MCP Server?
Install the server from GitHub, then add it to your claude_desktop_config.json with the command python -m src.mcp_server_openai.server. Set the OPENAI_API_KEY environment variable to your key and point PYTHONPATH to the server’s directory.
Key features of OpenAI MCP Server
- Queries OpenAI models directly from Claude
- Integrates via the Model Context Protocol
- Easy configuration in
claude_desktop_config.json - Simple Python-based setup and execution
Use cases of OpenAI MCP Server
- Using OpenAI’s GPT models as a fallback or alternative inside Claude
- Comparing OpenAI and Claude outputs without switching apps
- Automating tasks that require specific OpenAI model capabilities
FAQ from OpenAI MCP Server
What does OpenAI MCP Server do exactly?
It acts as an MCP server that Claude can call to send prompts to OpenAI’s API and return the model’s responses back to Claude.
What are the dependencies and runtime requirements?
You need Python, an OpenAI API key, and Claude Desktop (or any MCP client). The server runs as a local process using stdio transport.
How do I authenticate with OpenAI?
Set your OpenAI API key in the OPENAI_API_KEY environment variable inside the server’s configuration.
Where does my data live?
All data stays on your machine; the server sends prompts and receives responses directly via the OpenAI API. No data is stored locally by the server itself.
Are there any known limits or restrictions?
The README does not document specific limits. The server relies on your OpenAI API key’s rate limits and quotas.
Frequently asked questions
What does OpenAI MCP Server do exactly?
It acts as an MCP server that Claude can call to send prompts to OpenAI’s API and return the model’s responses back to Claude.
What are the dependencies and runtime requirements?
You need Python, an OpenAI API key, and Claude Desktop (or any MCP client). The server runs as a local process using stdio transport.
How do I authenticate with OpenAI?
Set your OpenAI API key in the `OPENAI_API_KEY` environment variable inside the server’s configuration.
Where does my data live?
All data stays on your machine; the server sends prompts and receives responses directly via the OpenAI API. No data is stored locally by the server itself.
Are there any known limits or restrictions?
The README does not document specific limits. The server relies on your OpenAI API key’s rate limits and quotas.
Basic information
More AI & Agents MCP servers
LinkedIn MCP Server
stickerdanielOpen-source MCP server for LinkedIn. Give Claude and any MCP-compatible AI agent access to profiles, companies, jobs, and messages.
Open Multi-Agent Canvas
CopilotKitThe open-source multi-agent chat interface that lets you manage multiple agents in one dynamic conversation and add MCP servers for deep research
MCP Client for Ollama (ollmcp)
joniglHarness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved pre
1MCP - One MCP Server for All
1mcp-appA unified Model Context Protocol server implementation that aggregates multiple MCP servers into one.
Mcp Agent
lastmile-aiBuild effective agents using Model Context Protocol and simple workflow patterns
Comments