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Expose an OpenAI-compatible endpoint to access and orchestrate MCP tools.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "MCP-Bridge" yet — see the docs or source repo.
I have an existing app that only supports the OpenAI API. Explain how to connect MCP tools through MCP-Bridge, including deployment steps, config examples, and the request flow.
An integration guide with architecture notes, sample configuration, and OpenAI-compatible calling patterns.
Help me design a tool-calling gateway based on MCP-Bridge so multiple AI clients can access internal MCP tools consistently, including authentication, logging, and rate-limiting suggestions.
A gateway design outlining service structure, key middleware capabilities, and operational recommendations.
My client cannot properly trigger MCP tools through MCP-Bridge. List common compatibility issues, debugging steps, and how to verify whether the OpenAI-style requests are correct.
A troubleshooting checklist covering request format, tool registration, log inspection, and validation methods.
Dynamically bridge and register MCP capabilities with two-way client communication.
Convert OpenAPI specs into MCP tools for fast LLM API integration.
Aggregate local MCP servers into one endpoint with runtime control and hot reload.
Build MCP servers quickly to expose app data and actions to AI clients.
Connect AI assistants to Jira, GitLab, and Confluence through one unified interface.
Register multiple AI endpoints and auto-route models by capability.