Agent Link MCP server

agent-link-mcp

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MCP server for bidirectional AI agent collaboration. Spawn and communicate with any AI coding agent CLI — Claude Code, Codex, Gemini, Aider, and more.

When to Use

• Stuck on a bug? — Your agent tried twice and failed. Let it ask another agent for a fresh perspective.
• Need a second opinion? — Get code review or architectural advice from a different AI model.
• Cross-model strengths — Use Claude for planning, Codex for execution, Gemini for research.
• Parallel work — Spawn multiple agents to tackle independent subtasks simultaneously.
• Rubber duck debugging — Have one agent explain the problem to another and get back a solution.

Use Cases

Get Help When Stuck

Your primary agent keeps failing on the same issue? Ask another agent:

# Claude Code is stuck on a TypeScript error it can't resolve.
# It spawns Codex for a second opinion:

spawn_agent("codex", "This TypeScript error keeps appearing. How do I fix it?", {
  error: "Type 'string' is not assignable to type 'number'",
  files: ["src/utils.ts"]
})

Cross-Agent Code Review

Have another model review your agent's code changes:

spawn_agent("claude", "Review these changes for bugs and edge cases", {
  files: ["src/api.ts", "src/handler.ts"],
  intent: "Code review before merge"
})

Multi-Agent Pipeline

Build a pipeline where agents handle different stages:

# Agent 1: Research
spawn_agent("gemini", "Find the best approach for WebSocket reconnection")

# Agent 2: Implementation (using Agent 1's advice)
spawn_agent("codex", "Implement WebSocket reconnection with exponential backoff", {
  files: ["src/ws-client.ts"]
})

# Agent 3: Review
spawn_agent("claude", "Review this implementation for production readiness", {
  files: ["src/ws-client.ts"]
})

Bidirectional Collaboration

Agents can ask questions back. The host answers, and work continues:

Host: spawn_agent("codex", "Add caching to the API layer")
Codex: [QUESTION] Should I use Redis or in-memory cache?
Host: reply("codex-a1b2c3", "Use Redis, we have it in our docker-compose")
Codex: [RESULT] Added Redis caching with 5-minute TTL...

Why

AI coding agents get stuck sometimes. Instead of waiting for you, they can ask another agent for help. agent-link-mcp lets any MCP-compatible agent spawn other agent CLIs as collaborators, exchange questions, and get results back — all through standard MCP tools.

• One-side install — only the host agent needs this MCP server. Spawned agents are just CLI subprocesses.
• Bidirectional — the host can ask questions to the spawned agent, and the spawned agent can ask questions back.
• Any agent — works with any CLI that accepts a prompt and returns text. Built-in profiles for Claude, Codex, Gemini, and Aider.
• Multi-agent — spawn multiple agents simultaneously for parallel collaboration.

Prerequisites

agent-link-mcp spawns other AI agents as CLI subprocesses. You need to install and authenticate the agent CLIs you want to collaborate with:

You only need the ones you plan to use. agent-link-mcp auto-detects which CLIs are installed.

Install

# Claude Code
claude mcp add agent-link npx agent-link-mcp

# Codex
codex mcp add agent-link npx agent-link-mcp

# Any MCP client
npx agent-link-mcp

Shortened. The full README is on GitHub.