Connect Your AI Client

Connect the IMVASA MCP server to Claude Desktop, Cursor, ChatGPT, Windsurf, Zed, VS Code extensions, or custom automated agents. Find your environment below for copy-ready configuration files and setup steps.

Server Endpoint URL

https://seoaudit.imvasa.dev/mcp

1. Claude Desktop

HTTP Transport

Open Claude Desktop Settings → Developer → Edit Config, or edit your configuration file directly:

macOS

~/Library/Application Support/Claude/claude_desktop_config.json

Windows

%APPDATA%\Claude\claude_desktop_config.json

Linux

~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "imvasa-audit": {
      "url": "https://seoaudit.imvasa.dev/mcp"
    }
  }
}

Restart Claude Desktop after saving. You'll see the IMVASA Audit Tool tools appear in the tool picker.

2. Cursor IDE

mcp.json

Add to ~/.cursor/mcp.json (globally) or .cursor/mcp.json in your project:

{
  "mcpServers": {
    "imvasa-audit": {
      "url": "https://seoaudit.imvasa.dev/mcp"
    }
  }
}

3. ChatGPT (Custom Connector)

Web / Desktop

Open ChatGPT Settings → Connectors / Developer Tools → Add Connector.
Paste the server URL: https://seoaudit.imvasa.dev/mcp
Save without authentication headers.
Enable the connector in a new chat and ask it to audit a URL.

4. Windsurf (Codeium)

mcp_config.json

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "imvasa-audit": {
      "serverUrl": "https://seoaudit.imvasa.dev/mcp"
    }
  }
}

5. Zed Editor

settings.json

In Zed user settings.json, add under context_servers:

{
  "context_servers": {
    "imvasa-audit": {
      "url": "https://seoaudit.imvasa.dev/mcp"
    }
  }
}

6. VS Code (Cline / Roo Code / Continue)

MCP Extension

Configure your MCP extension with the following definition:

{
  "mcpServers": {
    "imvasa-audit": {
      "url": "https://seoaudit.imvasa.dev/mcp",
      "disabled": false
    }
  }
}

7. Programmatic SDKs (Node.js & Python)

SDK Code

Connect custom automated agents, CI/CD scripts, or background workers using the official TypeScript and Python SDKs:

Node.js / TypeScript:

import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StreamableHttpClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";

const transport = new StreamableHttpClientTransport(new URL("https://seoaudit.imvasa.dev/mcp"));
const client = new Client({ name: "my-agent", version: "1.0.0" }, { capabilities: {} });
await client.connect(transport);

const result = await client.callTool({
  name: "run_audit",
  arguments: { url: "https://example.com" }
});

Python:

import asyncio
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client

async def run():
    async with streamablehttp_client("https://seoaudit.imvasa.dev/mcp") as (read, write):
        async with ClientSession(read, write) as session:
            await session.initialize()
            res = await session.call_tool("find_issues", arguments={"url": "https://example.com"})
            print(res.content[0].text)

asyncio.run(run())

8. Generic HTTP Clients & Other Tools

HTTP Stream

Any MCP client that supports Streamable HTTP transport can connect. Point it at the server URL above. No authentication headers are required.

Accept: application/json, text/event-stream
Content-Type: application/json