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MCP server setup

The Sympheny MCP server exposes the Sympheny API to AI assistants over the Model Context Protocol, so a model can create scenarios, run solver jobs, and read results without you wiring up HTTP calls yourself. It is a remote server, reachable over streamable HTTP.

Not yet available

The MCP server has not been released. The configuration below is the shape you will use once it ships — the server URL is a placeholder and will not connect today. Authentication settings will be added here when the server is published; the exact scheme is not final yet.

Throughout this page the placeholder endpoint is:

https://mcp.sympheny.com/mcp    # placeholder — not live yet

Claude Code

Add the server from the CLI (the --transport http flag is required for a remote server):

claude mcp add --transport http sympheny https://mcp.sympheny.com/mcp

To share the configuration with a team, use --scope project, which writes a checked-in .mcp.json:

{
  "mcpServers": {
    "sympheny": {
      "type": "http",
      "url": "https://mcp.sympheny.com/mcp"
    }
  }
}

Verify the connection with claude mcp get sympheny or the /mcp command.

Claude Desktop

Open Settings → Connectors → Add custom connector, enter the server URL, and click Add. This is the recommended path for remote servers — no config file to edit.

ChatGPT

Enable Developer mode, then open Settings → Connectors → Create and enter the server URL. When calling a model through the API instead, add the server as an MCP tool:

{
  "type": "mcp",
  "server_label": "sympheny",
  "server_url": "https://mcp.sympheny.com/mcp"
}

Gemini CLI

Add the server to ~/.gemini/settings.json under mcpServers, using httpUrl for the streamable-HTTP transport:

{
  "mcpServers": {
    "sympheny": {
      "httpUrl": "https://mcp.sympheny.com/mcp"
    }
  }
}

Not using an MCP client yet? Drive Sympheny with the REST API or the Python SDK today.