Admin Dashboard: MCP Servers

Model Context Protocol (MCP) is an open standard for connecting AI agents to external tools and data sources. The MCP Servers page lets you add, configure, and monitor MCP server connections.

Transport types

Type	Description
`stdio`	The engine spawns a local process and communicates over stdin/stdout. Best for npm packages and local scripts. Blocked in Cloud deployments (restricted by `MCPTransportPolicy`).
`sse`	The engine connects to a remote HTTP server via Server-Sent Events.
`http`	Streamable HTTP transport (current MCP standard). The engine sends HTTP requests to the server’s MCP endpoint. Best for modern hosted MCP servers.
`streamable-http`	Alias for `http`. Accepted for compatibility.

Adding from catalog

The catalog contains pre-configured, well-known MCP servers. Adding one is a one-click operation:

Click “Add from Catalog” on the MCP Servers page.
Browse or search for the server you need (GitHub, filesystem, PostgreSQL, etc.).
Click “Add” — the name, command, and args are pre-filled.
Fill in required environment variables (e.g., GITHUB_TOKEN) and save.
The engine spawns the process and discovers available tools automatically.

Adding a custom server

For servers not in the catalog, click “Add Custom” and fill in the form:

Name — unique identifier for referencing from agent configs.
Type — stdio, sse, http, or streamable-http.
Command / URL — for stdio: the command to run. For http/sse: the server URL.
Args — command-line arguments (stdio only).
Environment variables — key-value pairs passed to the process (stdio only).
Forward headers — list of HTTP header names to forward from the incoming chat request to the MCP server (SSE/HTTP only). Useful for multi-tenant MCP backends that need tenant context (e.g., X-Org-Id, X-User-Id).

# Stdio: Engine spawns the process (self-hosted only)
mcp_servers:
  github:
    command: npx
    args: ["-y", "@modelcontextprotocol/server-github"]
    env:
      GITHUB_TOKEN: ${GITHUB_TOKEN}

  # Python MCP server
  custom-tools:
    command: python
    args: ["-m", "my_mcp_server"]
    env:
      DATABASE_URL: ${DATABASE_URL}

# HTTP: Streamable HTTP transport (current MCP standard)
  tavily:
    type: http
    url: "https://mcp.tavily.com/mcp"
    env:
      TAVILY_API_KEY: ${TAVILY_API_KEY}

# SSE: Engine connects to a running server via Server-Sent Events
  analytics:
    type: sse
    url: "http://analytics-service:3000/mcp"

Monitoring and troubleshooting

Each MCP server shows a status indicator and the count of discovered tools:

Connected (green) — the server is running and tools are discovered.
Disconnected (red) — the server process crashed or the HTTP endpoint is unreachable.
Tools count — number of tools the server exposes. Click to see the full list with descriptions.