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agent mcp bridge

Name: agent mcp bridge
Author: ryno2390

作者 Ryne Schultz · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ⚠ suspicious

总下载

当前安装

版本数

在 OpenClaw 中安装

/install agent-mcp-bridge

功能描述

Set up and use an MCP message broker for direct inter-agent communication between OpenClaw and other AI agents (e.g. hermes-agent, Claude Code, any MCP-capab...

使用说明 (SKILL.md)

Agent MCP Bridge

A lightweight FastMCP + SQLite message broker that lets two AI agents communicate directly via MCP tools. Both agents connect to the same server as MCP clients — symmetric, no platform-specific adapters.

Architecture

Agent A (OpenClaw)          MCP Broker              Agent B (hermes-agent / any)
   send_message() ──────► FastAPI+SQLite ◄────────── poll_messages()
   poll_messages() ◄────── localhost:8765 ──────────► send_message()

Quick Setup

1. Install and start the broker

cp -r \x3Cskill-dir>/scripts/server/ ~/.openclaw/agent-bridge-mcp/
cd ~/.openclaw/agent-bridge-mcp
./start.sh   # creates venv, installs deps, starts on port 8765

2. Register as a launchd service (macOS auto-start)

cp \x3Cskill-dir>/references/launchd-plist.md ~/Library/LaunchAgents/ai.openclaw.agent-bridge.plist
# Edit the plist to set correct paths, then:
launchctl load ~/Library/LaunchAgents/ai.openclaw.agent-bridge.plist

3. Add to OpenClaw config

Add to ~/.openclaw/openclaw.json:

{
  "mcp": {
    "servers": {
      "agent-bridge": {
        "url": "http://127.0.0.1:8765/mcp",
        "transport": "streamable-http"
      }
    }
  }
}

4. Connect the other agent

Give the other agent the MCP URL: http://127.0.0.1:8765/mcp (streamable-http transport). They connect with their native MCP client support.

MCP Tools

Tool	Parameters	Returns	Use when
`send_message`	`from_agent`, `to`, `subject`, `body`, `reply_to?`	`{message_id, timestamp}`	Sending a task or reply
`poll_messages`	`agent_id`, `limit?`	list of message dicts	Checking your inbox
`mark_read`	`message_id`	`{status}`	After processing a message
`list_agents`	—	list of agent ids	Discovering who's active

Message format

{
  "id": "83223c09",
  "from_agent": "hermes",
  "to_agent": "isaac",
  "subject": "Research request",
  "body": "Please analyze...",
  "timestamp": "2026-03-31T16:58:31Z",
  "thread_id": "83223c09",
  "reply_to": null,
  "status": "pending"
}

Fallback: Filesystem bridge

If the MCP server is unavailable, use the filesystem bridge (zero infrastructure):

See references/filesystem-bridge.md for setup
Inbox/outbox dirs: ~/.openclaw/shared/{agent}-inbox/

Heartbeat integration (OpenClaw)

Add to HEARTBEAT.md to auto-process incoming messages:

Check ~/.openclaw/shared/isaac-inbox/ for new .json files.
If any exist: read, process, reply via hermes-inbox/, move to processed/.

Verification

Test the full loop:

# From Python
from agent_bridge import AgentBridge
bridge = AgentBridge("isaac")
bridge.send("hermes", "Handshake test", "Can you receive this?")
# Other agent polls and replies
msgs = bridge.receive()

安全使用建议

This skill appears coherent with its purpose, but review and accept the security tradeoffs before installing: 1) There is no authentication or encryption — any local user/process with file or loopback access can read messages; keep the broker confined to a single trusted user or network namespace. 2) start.sh will pip-install packages from PyPI into a created venv — inspect requirements.txt and the code before running. 3) The filesystem bridge writes JSON files and the server creates messages.db in the server directory; ensure those directories have appropriate ownership and permissions. 4) If you enable auto-start (launchd), edit the plist paths carefully and avoid running as a privileged user. 5) Consider running the broker in an isolated environment (dedicated user, container, or VM) or adding authentication/transport restrictions if you plan to expose the service beyond localhost. 6) Note the small implementation detail: AgentBridge defaults to using the package directory as the shared directory — if you want inboxes under ~/.openclaw/shared, pass that path explicitly when instantiating AgentBridge.

功能分析

Type: OpenClaw Skill Name: agent-mcp-bridge Version: 1.0.0 The bundle implements an inter-agent communication bridge using a local FastAPI/MCP server and a filesystem fallback. While the code appears functional and lacks clear malicious intent, it introduces high-risk capabilities including automated persistence via macOS launchd (`launchd-plist.md`) and instructions for the AI agent to autonomously poll, process, and respond to messages in the background (`SKILL.md`). These features, along with the setup of a local network service (`server.py`), fall under the category of risky capabilities that warrant a suspicious classification despite being aligned with the stated purpose.

能力评估

✓ Purpose & Capability

The name/description (MCP bridge for inter-agent messaging) aligns with the included server and filesystem-bridge code: a FastMCP + SQLite broker and a Python filesystem fallback. The only minor mismatch is that the AgentBridge default SHARED_DIR is Path(__file__).parent while the SKILL.md suggests using ~/.openclaw/shared; this is an implementation choice, not a functional contradiction.

ℹ Instruction Scope

SKILL.md instructs the user to copy the server files, run start.sh (which creates a venv and installs deps), optionally register a user launchd job, and add a local URL to OpenClaw config. The instructions do not ask the agent to read unrelated system files or external secrets. Note: message data is stored as plaintext (SQLite and JSON files) and the filesystem fallback writes to user-visible directories — there is no built-in authentication or encryption.

ℹ Install Mechanism

There is no formal install spec in the registry (instruction-only), but the included start.sh will create a virtualenv and pip-install requirements from PyPI (fastmcp, uvicorn, aiosqlite). This is a standard pattern but does entail network access to PyPI and execution of code you should audit before running.

✓ Credentials

The skill declares no required environment variables, credentials, or config paths, and the code does not reference external secrets. The scope of access (local filesystem and a local TCP port) is appropriate for a local message broker.

✓ Persistence & Privilege

always:false and default autonomous invocation are normal. The only persistence is user-level (virtualenv, SQLite DB, JSON files) and an optional per-user launchd plist. The skill does not attempt to modify other skills or system-wide privileged settings.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install agent-mcp-bridge
安装完成后，直接呼叫该 Skill 的名称或使用 /agent-mcp-bridge 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

Inter-agent MCP message broker — lets two AI agents on the same machine communicate directly via MCP tools (FastMCP + SQLite). Includes filesystem fallback bridge and macOS launchd auto-start.

元数据

Slug agent-mcp-bridge

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题

agent mcp bridge 是什么？

Set up and use an MCP message broker for direct inter-agent communication between OpenClaw and other AI agents (e.g. hermes-agent, Claude Code, any MCP-capab... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 86 次。

如何安装 agent mcp bridge？

在 OpenClaw 或 Claude Code 对话框中运行命令「/install agent-mcp-bridge」即可一键安装，无需额外配置。

agent mcp bridge 是免费的吗？

是的，agent mcp bridge 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。

agent mcp bridge 支持哪些平台？

agent mcp bridge 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。

谁开发了 agent mcp bridge？

由 Ryne Schultz（@ryno2390）开发并维护，当前版本 v1.0.0。