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Portkey MCP Gateway works with any MCP client. Connect your agents using a URL and API key.

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Find your connection URL

Go to MCP in your workspace sidebar. Click on a server to see its connection details. Each server has a URL: 
https://mcp.portkey.ai/{server-slug}/mcp
Copy this URL to use in your agent configuration.
For self-hosted deployments, replace mcp.portkey.ai with your gateway URL.

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Claude Desktop

Add to your Claude Desktop config file. macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json 
{
  "mcpServers": {
    "linear": {
      "url": "https://mcp.portkey.ai/linear/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_PORTKEY_API_KEY"
      }
    }
  }
}
Restart Claude Desktop after saving. The tools appear in your conversation. If the server uses OAuth, Claude prompts you to authenticate when you first use a tool.

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Cursor

Open Cmd/Ctrl + Shift + P > Cursor Settings: Open MCP Settings. 
{
  "mcpServers": {
    "linear": {
      "url": "https://mcp.portkey.ai/linear/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_PORTKEY_API_KEY"
      }
    }
  }
}
The tools are available in Cursor’s agent mode.

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VS Code

With GitHub Copilot and the MCP extension: 
{
  "mcp.servers": {
    "linear": {
      "url": "https://mcp.portkey.ai/linear/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_PORTKEY_API_KEY"
      }
    }
  }
}

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Python

pip install mcp

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

url = "https://mcp.portkey.ai/linear/mcp"
headers = {"Authorization": "Bearer YOUR_PORTKEY_API_KEY"}

async with streamablehttp_client(url, headers=headers) as (read, write, _):
    async with ClientSession(read, write) as session:
        await session.initialize()
        
        # List tools
        tools = await session.list_tools()
        for tool in tools.tools:
            print(f"{tool.name}: {tool.description}")
        
        # Call a tool
        result = await session.call_tool(
            "create_issue",
            {"title": "Bug report", "priority": "high"}
        )
        print(result)

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TypeScript

npm install @modelcontextprotocol/sdk

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

const transport = new StreamableHTTPClientTransport(
  new URL("https://mcp.portkey.ai/linear/mcp"),
  {
    requestInit: {
      headers: { "Authorization": "Bearer YOUR_PORTKEY_API_KEY" }
    }
  }
);

const client = new Client({ name: "my-agent", version: "1.0.0" });
await client.connect(transport);

const tools = await client.listTools();
console.log(tools);

const result = await client.callTool({
  name: "search_issues",
  arguments: { query: "bug" }
});
console.log(result);

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API keys

Create API keys in Settings > API Keys. Keys are scoped to teams, so the key determines which MCP servers your agent can access.

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Handling OAuth

If an MCP server uses OAuth for per-user authentication, users need to complete OAuth consent before using tools. The first time a user calls a tool, Portkey returns an error with an authorization URL. Redirect the user to complete OAuth. After consent, retry the request. 
try:
    result = await session.call_tool("get_repos", {})
except Exception as e:
    if "authorization_url" in str(e):
        # Redirect user to authorize
        print(f"Please authorize: {authorization_url}")
After authorization, Portkey stores the user’s tokens and handles refresh automatically.

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AI Gateway integration

If you use Portkey’s AI Gateway for LLM calls, MCP integrates automatically:
  • Unified dashboard for LLM and MCP activity
  • Traces span model calls and tool use
  • Single API key for both services