This package is officially distributed via: - **PyPI**: https://pypi.org/project/mcp-server-openai-bridge/ - **GitHub**
If you already use Openai Bridge, the openai bridge mcp server is the piece that lets your assistant work with it directly. This package is officially distributed via: - PyPI: https://pypi.org/project/mcp-server-openai-bridge/ - GitHub: https://github.com/jaspertvdm/mcp-server-openai-bridge.
Installation goes through your MCP client rather than a global install: point it at mcp-server-openai-bridge on PyPI and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
Configuration is passed through the environment: OPENAI_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. It is maintained by jaspertvdm; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
{
"mcpServers": {
"server-openai-bridge": {
"command": "uvx",
"args": ["mcp-server-openai-bridge"],
"env": {
"OPENAI_API_KEY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| OPENAI_API_KEY | Credential the server authenticates with. | Yes |
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