Skip to main content
After deployment, each app is reachable at an HTTPS endpoint such as: 
https://<app_id>.deployments.mcp-agent.com

Replace `<app_id>` with the hostname shown by `mcp-agent deploy` or `mcp-agent cloud servers describe` (e.g., `app_abc123xyz.deployments.mcp-agent.com`).
This page explains how to retrieve the URL, set up authentication, configure clients, and script interactions.

​
1. Find the server URL

# Show all deployments (filterable, sortable)
mcp-agent cloud servers list

# Describe a specific deployment and copy the Server URL
mcp-agent cloud servers describe app_abc123 --format text
The description output includes:
  • Server URL – base URL (append /sse for SSE transport or /call_tool for HTTP).
  • Authentication mode (Bearer token, unauthenticated, OAuth coming soon).
  • Status, creation time, description.

​
2. Make sure clients have the right secrets

If you tagged any !user_secret entries, each consumer must configure the deployment before connecting: 
# Prompts for required secrets (per API key)
mcp-agent cloud configure --id https://<app_id>.deployments.mcp-agent.com

# Inspect required parameters without storing
mcp-agent cloud configure --id <server-url> --params
You can supply a YAML file (--secrets-file) or capture the resulting file (--secrets-output-file) to share with your team.

​
3. Install into MCP clients

Use the top-level install command to update client-specific config files: 
# Claude Desktop (macOS, Windows, Linux)
    mcp-agent install https://<app_id>.deployments.mcp-agent.com/sse \
  --client claude_desktop --name web-summarizer

# Cursor
    mcp-agent install https://<app_id>.deployments.mcp-agent.com/sse \
  --client cursor

# VS Code MCP extension
    mcp-agent install https://<app_id>.deployments.mcp-agent.com/sse \
  --client vscode

# Claude Code (codespaces experience)
    mcp-agent install https://<app_id>.deployments.mcp-agent.com/sse \
  --client claude_code

# ChatGPT Apps (requires --no-auth deployments)
    mcp-agent install https://<app_id>.deployments.mcp-agent.com/sse \
  --client chatgpt
What the command does:
  • Validates your MCP_API_KEY (or uses --api-key).
  • Fetches app metadata (name, unauthenticated status) for validation.
  • Writes the appropriate JSON snippet to the client-specific config file.
  • Masks secrets when printing to the terminal (use --dry-run to preview).
Client config locations:
• Claude Desktop – ~/Library/Application Support/Claude/claude_desktop_config.json (macOS)
• Cursor – ~/.cursor/mcp.json
• VS Code – <workspace>/.vscode/mcp.json
• Claude Code – ~/.claude.json

​
4. Manual configuration (if needed)

All MCP clients understand the same HTTP/SSE interface. A minimal configuration looks like: 
{
  "servers": {
    "web-summarizer": {
      "url": "https://<app_id>.deployments.mcp-agent.com/sse",
      "headers": {
        "Authorization": "Bearer ${MCP_API_KEY}"
      }
    }
  }
}
For Claude Desktop (stdio-only), wrap the HTTP server with mcp-remote: 
{
  "servers": {
    "web-summarizer": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://<app_id>.deployments.mcp-agent.com/sse",
        "--header",
        "Authorization: Bearer ${MCP_API_KEY}"
      ]
    }
  }
}

​
5. Automate calls from code

​
Python

  1. Create or update a server entry in mcp_agent.config.yaml: 
    mcp:
  servers:
    web_summarizer_cloud:
      transport: sse
      url: "https://<app_id>.deployments.mcp-agent.com/sse"
      headers:
        Authorization: "Bearer ${MCP_API_KEY}"
  2. Use the shared server registry to open a client session: 
    import asyncio
from mcp_agent.config import get_settings
from mcp_agent.mcp.mcp_server_registry import ServerRegistry
from mcp_agent.mcp.gen_client import gen_client

async def run_workflow():
    registry = ServerRegistry(config=get_settings())
    async with gen_client("web_summarizer_cloud", server_registry=registry) as client:
        launch = await client.call_tool(
            "workflows-WebSummarizerWorkflow-run",
            arguments={"run_parameters": {"url": "https://example.com"}},
        )
        run_id = launch.content[0].text
        status = await client.call_tool(
            "workflows-get_status",
            arguments={"run_id": run_id},
        )
        print(status.content[0].text)

asyncio.run(run_workflow())

​
HTTP / cURL

curl -X POST https://<app_id>.deployments.mcp-agent.com/call_tool \
  -H "Authorization: Bearer $MCP_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "workflows-WebSummarizerWorkflow-run",
    "arguments": {"run_parameters": {"url": "https://example.com"}}
  }'

​
MCP Inspector

npx @modelcontextprotocol/inspector \
  --transport sse \
  --server-url https://<app_id>.deployments.mcp-agent.com/sse \
  --header "Authorization: Bearer $MCP_API_KEY"

​
6. Provide usage instructions to end users

Consider sharing a short README with:
  • The server URL and description.
  • Required user secrets (from mcp-agent cloud configure --params).
  • Example calls (like the snippets above).
  • Recommended MCP clients (Claude Desktop, Cursor, ChatGPT, etc.).
  • Observability tips (mcp-agent cloud logger tail for debugging).

​
7. Rotate tokens and access

  • Rotate API keys – run mcp-agent login again or set a new MCP_API_KEY.
  • Revoke access – delete individual configurations (coming soon) or redeploy with --auth to disable unauthenticated access.
  • Publish publicly – ensure the deployment is unauthenticated and document explicit rate limits / expectations.
⌘I