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A
Ai Agent Bridge MCP
by @jliucode
GitHub Repo(1 stars)

A bridge for AI agents — real-time communication, task delegation, and status monitoring via the MCP protocol.

Created 5/6/2026
Updated about 3 hours ago
README
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Repository documentation and setup instructions

AI Agent Bridge MCP

A bridge for AI agents — real-time communication, task delegation, and status monitoring via the MCP protocol.

Quick Start

Backend Server

# Install dependencies
pip install -e .

# Start the server
python main.py
# Server running at http://localhost:8000

Client (MCP Proxy)

The client component connects AI agents (like Claude Code) to the Bridge Server:

cd client

# Install dependencies
pip install -e .

# Create .env file (optional)
cat > .env << EOF
BRIDGE_URL=ws://localhost:8000/ws_proxy
LOG_LEVEL=INFO
EOF

# Start the MCP Proxy
python main.py

Configure Claude Code to use the proxy:

{
  "mcpServers": {
    "agent-bridge-proxy": {
      "command": "python",
      "args": ["F:/path/to/client/main.py"]
    }
  }
}

Frontend Dashboard

cd frontend
npm install
npm run dev
# Dev server at http://localhost:3000 (API proxied to :8000)

Docker

docker build -t ai-agent-bridge .
docker run -p 8000:8000 ai-agent-bridge

Architecture

📖 For detailed technical architecture documentation, see ARCHITECTURE.md.

┌─────────────────────────────────────────────────────────────────┐
│                        Frontend Dashboard                        │
│                    (Vue 3 + WebSocket + Pinia)                   │
└─────────────────────────────────────────────────────────────────┘
                               │
                               │ WebSocket
                               ▼
┌─────────────────────────────────────────────────────────────────┐
│                         Bridge Server                            │
│                   (FastAPI + SSE + JSON-RPC)                     │
│                                                                 │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────────────┐  │
│  │ Agent Registry│  │Task Manager │  │ WebSocket Proxy API  │  │
│  └──────────────┘  └──────────────┘  └──────────────────────┘  │
└─────────────────────────────────────────────────────────────────┘
                               │
               ┌───────────────┼───────────────┐
               │               │               │
               │ SSE           │ WS Proxy      │ SSE
               ▼               ▼               ▼
┌───────────────────┐  ┌───────────────────┐  ┌───────────────────┐
│  Claude Code A    │  │   MCP Proxy      │  │  Claude Code B    │
│  (Direct SSE)     │  │ (Client Agent)   │  │  (Direct SSE)     │
└───────────────────┘  └───────────────────┘  └───────────────────┘

Client Component (MCP Proxy)

The client (client/) provides an MCP Proxy that allows Claude Code instances to:

  • Register themselves with the Bridge
  • List remote agents across different machines
  • Delegate tasks to other agents
  • Receive and handle assigned tasks
  • Update task status and results

Client Tools

| Tool | Description | |------|-------------| | agent_register | Register/update agent info (project, skills, capabilities) | | get_pending_tasks | Get pending tasks for current agent | | list_remote_agents | List agents on other machines | | task_delegate | Delegate task to another project's agent | | task_update | Update task status (IN_PROGRESS, DONE, FAILED) |

Client Configuration

| Variable | Default | Description | |----------|---------|-------------| | BRIDGE_URL | ws://localhost:8000/ws_proxy | WebSocket proxy endpoint | | LOG_LEVEL | INFO | Logging level | | LLM_ENABLED | false | Enable LLM routing | | LLM_PROVIDER | qwen | LLM provider (qwen, moonshot) | | DASHSCOPE_API_KEY | — | DashScope API key for LLM |

Usage

Agent Registration & Connection

Agents connect via SSE + JSON-RPC 2.0 protocol:

1. Connect to SSE to get a session ID

curl -N http://localhost:8000/sse
# → event: session
# → data: {"session_id": "abc123..."}

2. Register the agent

curl -X POST "http://localhost:8000/messages?session_id=abc123..." \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": "1",
    "method": "agent.register",
    "params": {
      "name": "claude-code",
      "project": "my-project",
      "capabilities": {
        "mcp_servers": ["gitnexus", "zread"],
        "skills": ["pptx", "commit"],
        "description": "Code generation and bug fixing"
      }
    }
  }'

Once registered, the Dashboard will show this agent's status, project, IP, and capability badges in real time.

3. Send heartbeats to stay online

curl -X POST "http://localhost:8000/messages?session_id=abc123..." \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc": "2.0", "id": "2", "method": "agent.heartbeat"}'

Agents are auto-marked OFFLINE after 60 seconds without a heartbeat.

Task Delegation

Agent A can delegate a task to Agent B and receive real-time results:

1. Delegate a task

curl -X POST "http://localhost:8000/messages?session_id=<agent-a-session>" \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": "3",
    "method": "task.delegate",
    "params": {
      "title": "Fix login bug",
      "description": "Login endpoint returns 500 on null input",
      "to_agent": "<agent-b-id>"
    }
  }'

2. Update task progress and result

Agent B receives a task.assigned event via SSE, then updates the task:

# Start working
curl -X POST "http://localhost:8000/messages?session_id=<agent-b-session>" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc": "2.0", "id": "4", "method": "task.update", "params": {"task_id": "<task-id>", "status": "IN_PROGRESS"}}'

# Complete with result
curl -X POST "http://localhost:8000/messages?session_id=<agent-b-session>" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc": "2.0", "id": "5", "method": "task.update", "params": {"task_id": "<task-id>", "status": "DONE", "result": "Fixed: added null check"}}'

Agent A receives task.updated and task.result events via SSE in real time.

Claude Code Integration

Claude Code connects to this bridge via the standard MCP SSE protocol. Once connected, it appears on the Dashboard and can exchange tasks with other agents.

1. Configure Claude Code

Create a .mcp.json in your project root (or use the /mcp command in Claude Code):

{
  "mcpServers": {
    "agent-bridge": {
      "type": "sse",
      "url": "http://localhost:8000/sse"
    }
  }
}

2. Auto-register after connecting

Once connected, ask Claude Code:

Use the agent_register tool to register this agent. Set name to "claude-code-01", project to "my-project", and list your MCP servers and skills under capabilities.

Claude Code calls agent_register to register. After registration:

  • This Claude Code instance appears on the Dashboard with status, project, and capability badges
  • Use agent_list to see all online agents
  • Use task_delegate to send tasks to other agents
  • Receive real-time task updates from other agents via SSE

3. List all agents

Use agent_list to show all currently connected agents

4. Delegate a task to another agent

Use task_delegate to send "Fix null pointer in login endpoint" to agent-b (ID: xxx). Description: The login endpoint returns 500 when given null input.

5. Receive results from other agents

When the target agent completes the task, Claude Code receives a task.result event via SSE and can report it in the conversation.

6. Send heartbeats

Use agent_heartbeat to send a heartbeat

Consider adding heartbeat calls to a cron hook for automatic keep-alive every 30 seconds.

Web Dashboard

Open http://localhost:3000 to see:

  • StatsBar: Total agents, online/busy counts, task statistics
  • AgentDashboard: Agent cards showing status, project, IP, current task, and MCP/Skill tags
  • TaskPanel: Live task list with delegation flow and execution status

Features

  • MCP JSON-RPC 2.0 over SSE — Real-time bidirectional agent communication
  • Task delegation & tracking — Cross-agent task dispatch, status sync, result delivery
  • Live Dashboard — Vue 3 real-time display of agent status, capability matrix, task flow
  • Agent registry — Heartbeat monitoring, auto-offline detection, state management
  • REST API — Query agents, tasks, and statistics
  • WebSocket push — Real-time frontend updates
  • MCP Proxy Client — Enable Claude Code on any machine to join the bridge

Project Structure

ai-agent-bridge-mcp/
  main.py               # Entry point — uvicorn runner
  config.py             # Logging & LLM configuration
  pyproject.toml        # Project metadata & dependencies
  Dockerfile            # Docker build
  backend/
    server.py           # FastAPI app, SSE/WS endpoints
    mcp_handler.py      # MCP JSON-RPC 2.0 over SSE
    agent_registry.py   # Agent CRUD, heartbeat, state
    task_manager.py     # Task lifecycle, delegation
    models.py           # Pydantic data models
    routes.py           # REST API routes
  client/
    main.py             # Client entry point
    config.py           # Client configuration
    bridge_client.py    # WebSocket client to Bridge
    mcp_server.py       # MCP Proxy Server
    agent_manager.py    # Local agent management
    remote_agents_cache.py  # Remote agent cache
    llm_router.py       # LLM routing (optional)
    tools/
      agent_tools.py    # Agent registration tools
      task_tools.py     # Task delegation tools
      remote_skill.py   # Remote skill invocation
    utils/
      logger.py         # Logging utilities
      file_transfer.py  # File transfer utilities
  frontend/
    src/
      App.vue           # Root layout
      api/index.js      # REST + WebSocket client
      components/
        AgentDashboard.vue  # Agent card grid
        AgentCard.vue       # Single agent status card
        TaskPanel.vue       # Task list panel
        CapabilityBadge.vue # MCP/Skill tag badge
        StatusIndicator.vue # Online status dot
        StatsBar.vue        # Summary statistics bar
      stores/           # Pinia state management

API Endpoints

| Method | Path | Description | |--------|------|-------------| | GET | /health | Health check | | GET | /api/agents | List all agents | | GET | /api/agents/{id} | Get agent details | | GET | /api/tasks | List tasks (optional ?from_agent= ?to_agent=) | | GET | /api/tasks/{id} | Get task details | | GET | /api/stats | Dashboard statistics | | GET | /sse | SSE endpoint (agent connects here) | | POST | /messages?session_id= | JSON-RPC messages from agents | | WS | /ws | WebSocket for frontend real-time updates | | WS | /ws_proxy | WebSocket proxy for client agents |

MCP Methods

Agent Methods

| Method | Description | |--------|-------------| | agent.register | Register with name, project, capabilities | | agent.heartbeat | Periodic keep-alive | | agent.update_status | Change status (ONLINE/BUSY/IDLE) | | agent.list | List all registered agents |

Task Methods

| Method | Description | |--------|-------------| | task.delegate | Send a task to another agent | | task.update | Update task status and result | | task.list | List tasks for this agent |

Standard MCP

| Method | Description | |--------|-------------| | tools/list | List available MCP tools |

Environment Variables

| Variable | Default | Description | |----------|---------|-------------| | SERVER_HOST | 0.0.0.0 | Bind address | | SERVER_PORT | 8000 | Server port | | MOONSHOT_API_KEY | — | Moonshot LLM API key | | DASHSCOPE_API_KEY | — | DashScope (Qwen) API key | | DASHSCOPE_MODEL_NAME | qwen-max | DashScope model name | | DEFAULT_OUTPUT_DIR | output | Default output directory |

Dual Remote Push

git push origin
git push github --all

License

MIT License - see LICENSE for details.

Quick Setup
Installation guide for this server

Install Package (if required)

uvx ai-agent-bridge-mcp

Cursor configuration (mcp.json)

{ "mcpServers": { "jliucode-ai-agent-bridge-mcp": { "command": "uvx", "args": [ "ai-agent-bridge-mcp" ] } } }