API Development stdio

Bifrost

Name: Bifrost
Author: maximhq

Created by maximhq

Provides a high-performance, resilient AI gateway for connecting to multiple large language model providers through a single, unified API.

How to Connect & Install

Select your client or environment below to copy the verified, ready-to-run installation configuration.

1-line autonomous agent setup instruction. Paste into Claude Code, Codex CLI, or Cursor Agent:

Fetch and configure Model Context Protocol (MCP) server Bifrost from https://www.fastmcp.dev/server/bifrost

Agents automatically discover, install, and execute the server spec without manual token setup.

Connect via direct Stateless MCP v2 / Streamable HTTP endpoint or JSON-RPC:

https://github.com/maximhq/bifrost

Stateless edge endpoint compliant with MCP 2024-11-05 and v2 draft protocol specs.

Includes server instructions and tool definitions for Claude:

claude mcp add bifrost -- npx -y bifrost

Run in terminal to register server in current project or pass --scope user for global availability.

Configures server instructions and tools for OpenAI Codex & ChatGPT Desktop:

[mcp_servers.bifrost]
command = "npx"
args = ["-y","bifrost"]

Applies to ChatGPT Desktop app, Codex CLI, and IDE extension across your Codex host.

Add to Cursor project settings (.cursor/mcp.json) or Cursor Settings > Features > MCP:

{
  "mcpServers": {
    "bifrost": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "bifrost"
      ]
    }
  }
}

Commit to version control to allow teammates to connect immediately.

Install as an autonomous Agent Skill using the standard skills CLI:

npx skills add https://github.com/maximhq/bifrost

Standard agent skill installer compatible with Claude Code, Cursor, and agy harnesses.

Server Guidance & Instructions OpenAI & Claude Spec Compliant

Bifrost: Provides a high-performance, resilient AI gateway for connecting to multiple large language model providers through a single, unified API. Key capabilities: Built-in Model Context Protocol (MCP) support for external tool integration; Native Prometheus metrics for built-in observability.

Codex and Claude read this instruction prompt during initialization to orchestrate cross-tool workflows and rate limits.

Top Core Functions

01 Connect multiple large language models

02 Balance traffic across different providers

03 Observe metrics through native integration