vela-mcp
MCP server that exposes Vela RemotePC endpoints as tools, allowing AI clients to control the host system.
README
Vela MCP Server
MCP (Model Context Protocol) server that exposes Vela RemotePC endpoints as tools, so AI clients (Claude Desktop, Cline, Cursor, Gemini, etc.) can control remote systems.
Architecture
The server supports two transport modes that share the same 150+ tool definitions (tools.py):
1. STDIO (single-tenant, per-process)
Each process is bound to one agent via environment variables. Run multiple agents by defining multiple entries in mcp_settings.json, each with its own env block.
MCP client config (cline_mcp_settings.json or claude_desktop_config.json):
{
"mcpServers": {
"vela-home": {
"command": "/path/to/.venv/bin/mcp",
"args": ["run", "vela_mcp/tools.py:mcp"],
"cwd": "/path/to/vela-mcp",
"env": {
"VELA_API_URL": "https://vela.mikesplore.tech",
"VELA_TOKEN": "<relay_secret>",
"AGENT_ID": "agt_123"
}
},
"vela-work": {
"command": "/path/to/.venv/bin/mcp",
"args": ["run", "vela_mcp/tools.py:mcp"],
"cwd": "/path/to/vela-mcp",
"env": {
"VELA_API_URL": "https://vela.mikesplore.tech",
"VELA_TOKEN": "<relay_secret>",
"AGENT_ID": "agt_456"
}
}
}
}
2. HTTP (multi-tenant, shared server)
A single server instance handles any number of agents. No per-agent env vars needed. The caller provides agent_id and relay_secret in one of two ways:
Claude.ai connector (only accepts a URL — secret goes in the path):
https://mcp.mikesplore.tech/mcp/agt_123:<relay_secret>
Local clients (Cline/Claude Desktop — accept headers):
url: https://mcp.mikesplore.tech/mcp/agt_123
headers: { "Authorization": "Bearer <relay_secret>" }
The server eagerly validates the credentials against the relay on session start, then forwards all tool calls through the relay — which enforces tenant isolation on every request.
How multi-tenancy works
- vela-mcp does not store agent credentials. It extracts
agent_idfrom the URL path andrelay_secretfrom theAuthorizationheader on each incoming request. - velavps (the relay server) enforces isolation:
_verify_agent_access(agent_id, secret)rejects requests where the secret doesn't match the agent's registered secret, or where the agent belongs to another user. - 150+ tools are untouched — they call
vela_client.get/post/…which resolves to either the per-request or per-process client automatically.
Quick Start
python -m vela_mcp.server
Server starts on http://0.0.0.0:8002 with the MCP endpoint at /mcp/{agent_id}.
Setup
- Copy
.env.exampleto.env - Set
VELA_API_URL— your Vela relay VPS host (e.g.https://vela.mikesplore.tech) - For stdio mode: also set
VELA_TOKEN(relay secret) andAGENT_ID - For HTTP mode: you only need
VELA_API_URLandPORT; credentials come from the client
Run Script
./run.sh # start the MCP server (HTTP/streamable transport)
./run.sh dev # start the MCP Inspector (dev/testing UI)
Project Layout
vela_mcp/
__init__.py
config.py # Settings (VELA_API_URL, VELA_TOKEN, AGENT_ID, PORT)
client.py # RelayConnection, VelaClient, per-request contextvar proxy
server.py # FastAPI app with multi-tenant middleware at /mcp/{agent_id}
tools.py # 150+ MCP tool definitions (unchanged)
Development
.venv/bin/mcp dev vela_mcp/tools.py:mcp
Requirements
- Python >= 3.10
mcp >= 1.0.0fastapi >= 0.110.0httpx >= 0.27.0pydantic-settings >= 2.0.0uvicorn >= 0.30.0
推荐服务器
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。
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。
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。
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。
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。
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。
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。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
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。