vela-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@vela-mcpwhat's the current CPU usage on the remote host?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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.
Related MCP server: allcanuse-mcp
Quick Start
python -m vela_mcp.serverServer starts on http://0.0.0.0:8002 with the MCP endpoint at /mcp/{agent_id}.
Setup
Copy
.env.exampleto.envSet
VELA_API_URL— your Vela relay VPS host (e.g.https://vela.mikesplore.tech)For stdio mode: also set
VELA_TOKEN(relay secret) andAGENT_IDFor 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:mcpRequirements
Python >= 3.10
mcp >= 1.0.0fastapi >= 0.110.0httpx >= 0.27.0pydantic-settings >= 2.0.0uvicorn >= 0.30.0
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