MSG - MCP Swarm Gateway

MSG - MCP Swarm Gateway

Turns web-based AIs into full-powered agents with local PC access, 33 tools across 8 categories, and parallel swarm orchestration with real-time validation.

Category
访问服务器

README

MSG - MCP Swarm Gateway

Universal MCP Bridge + Multi-Agent Swarm Orchestrator

Turn any web-based AI (ChatGPT, Claude, Grok, Kimi, DeepSeek, Gemini) into a full-powered agent with access to your local PC, terminal, browser, and code execution - with a swarm of parallel agents validated in real-time.


What Makes MSG Different

Feature MCP SuperAssistant Other Tools MSG
Web AI Chat Support 11 platforms 2-5 11+ platforms
Local MCP Tools ~10 Varies 33 tools, 8 categories
Multi-Agent Swarm No No Yes - parallel agents
Parallel Validation No (just pytest) No Review agents + pytest
Custom Skills/Plugins No Limited Hot-loadable skill system
Web Dashboard No No Real-time monitoring
Browser Extension Yes No Yes (11 platforms)

Architecture

Web AI Chats (ChatGPT, Claude, Grok, Kimi, DeepSeek, Gemini...)
         |
    HTTP/WebSocket (CORS-enabled)
         |
    +----v--------------+---------------+
    |   MSG GATEWAY     |  SWARM ORCH.  |
    |   (FastAPI)       |  (Parallel)   |
    +----v--------------+---------------+
         |
    +----v--------------+
    |  MCP LOCAL TOOLS  |
    |  (33 tools)       |
    +----v--------------+
    |  Your PC          |
    |  Files, Terminal  |
    |  Browser, Code    |
    +-------------------+

Quick Start

1. Install Dependencies

pip install mcp[cli] fastapi uvicorn websockets pyyaml jinja2 psutil httpx

Optional (for browser tools):

pip install playwright
playwright install chromium

2. Run MSG

cd msg
python run.py

The dashboard will be available at:

  • Dashboard: http://localhost:8765/dashboard
  • API Docs: http://localhost:8765/docs
  • Tool Explorer: http://localhost:8765/tools

3. Install Browser Extension

  1. Open Chrome/Firefox extensions page
  2. Enable "Developer mode"
  3. Click "Load unpacked" and select the extension/ folder
  4. The MSG tool panel will appear on supported AI chat sites

4. Connect Your AI Chat

Option A: Browser Extension (Recommended)

The extension automatically injects MCP tool capabilities into:

  • ChatGPT (chatgpt.com)
  • Claude (claude.ai)
  • Grok (grok.x.ai)
  • Kimi (kimi.ai)
  • DeepSeek (chat.deepseek.com)
  • Gemini (gemini.google.com)
  • Perplexity (perplexity.ai)
  • Mistral (chat.mistral.ai)
  • OpenRouter (openrouter.ai)
  • T3 Chat (t3.chat)

Option B: Direct API

Send tool calls directly from any app:

curl -X POST http://localhost:8765/api/v1/tools/execute_command \
  -H "Content-Type: application/json" \
  -d '{"params": {"command": "ls -la"}}'

Option C: WebSocket (Real-time)

const ws = new WebSocket('ws://localhost:8765/ws');
ws.send(JSON.stringify({
    tool: 'read_file',
    params: {path: '/path/to/file.txt'}
}));
ws.onmessage = (e) => console.log(JSON.parse(e.data));

33 Built-in MCP Tools

Filesystem (8)

Tool Description
read_file Read text file with optional offset/limit
write_file Write or overwrite a file
append_file Append content to a file
list_directory List files with metadata (size, mtime)
search_files Recursive glob search
create_directory Create directory structure
delete_path Delete file or directory
get_file_info Size, modified time, permissions

Terminal (3)

Tool Description
execute_command Run shell command with timeout (security sandboxed)
execute_script Run a script file
start_background_process Start daemon process, return PID

Browser (4)

Tool Description
browser_visit Navigate to URL, get page content
browser_click Click element by selector
browser_input Fill form input
browser_screenshot Capture page screenshot

Code Execution (3)

Tool Description
run_python Execute Python code in isolated subprocess
run_javascript Execute JS via Node.js
evaluate_expression Evaluate math/code expressions

System (4)

Tool Description
get_system_info CPU, RAM, disk, OS info
list_processes Running processes
kill_process Kill process by PID
search_web Web search via DuckDuckGo

Git (4)

Tool Description
git_status Repository status
git_log Commit history
git_diff Current diff
git_exec Run any git command

Docker (4)

Tool Description
docker_ps List containers
docker_exec Execute in container
docker_logs Container logs
docker_run Run new container

Dev Tools (3)

Tool Description
npm_install npm install
pip_install pip install
run_tests Run pytest/jest

Swarm Orchestrator

The swarm executes complex projects with parallel validation:

  1. You submit a project: "Build a Python web scraper"
  2. Project Manager decomposes it into tasks
  3. Code Agents (parallel) write the code
  4. Review Agents (parallel) validate each batch - checking syntax, docstrings, error handling
  5. Verdict: PASS / WARNING / REVISE
  6. Debug Agent fixes REVISE items
  7. Test Agent runs integration tests
  8. Results delivered

Parallel Validation (The Key Feature)

Unlike other systems that only run pytest after code is done, MSG runs Review Agents in parallel with Code Agents. While one agent is still writing code, another is already reviewing what was just completed. This catches issues immediately, not after hours of work.

Submit a Swarm Task

curl -X POST http://localhost:8765/api/v1/swarm/task \
  -H "Content-Type: application/json" \
  -d '{"description": "Build a calculator app", "files": ["calc.py", "test_calc.py"]}'

Check status:

curl http://localhost:8765/api/v1/swarm/task/{task_id}

Configuration

Edit config.yaml:

gateway:
  host: "0.0.0.0"
  port: 8765

security:
  allowed_directories:
    - "/home/yourname/projects"
  blocked_commands:
    - "rm -rf /"
  max_execution_time: 30

swarm:
  max_parallel_agents: 5
  review_strictness: "strict"

Security

  • Path sandboxing: Tools can only access allowed directories
  • Command blocklist: Dangerous commands are rejected
  • Execution timeouts: No infinite hangs
  • Output limits: Prevents memory exhaustion
  • Optional auth: Token-based API authentication

Tech Stack

Component Technology
MCP Server mcp (FastMCP) Python SDK
Gateway FastAPI + WebSockets
Process Mgmt asyncio + subprocess
Browser Playwright
Message Bus asyncio Queue
Dashboard FastAPI + Jinja2 + vanilla JS
Extension Vanilla JS (content script)

Project Stats

  • 34 Python files, 3,693 lines of code
  • 33 MCP tools across 8 categories
  • 5 agent types in the swarm (coder, reviewer, tester, debugger + orchestrator)
  • 11 AI platforms supported via browser extension
  • 6 dashboard pages with real-time WebSocket updates
  • 100% syntax clean - all files pass py_compile

License

MIT - Use it, modify it, make money with it. Go get 'em.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选