Help Scout

Connect AI agents to Help Scout for customer support, conversation management, and mailbox operations

Prerequisites Before you begin, create an account and get your API Key.

Getting started

Connect to Help Scout to manage customer support and conversation management through AI agents.

API

1. Install the SDKs (optional)

   pip

   pip install klavis
   
2. Create a Strata MCP Server with Help Scout

   Python

   from klavis import Klavis
   from klavis.types import McpServerName
   
   klavis_client = Klavis(api_key="YOUR_API_KEY")
   
   # Create a Strata MCP server with Help Scout
   response = klavis_client.mcp_server.create_strata_server(
       servers=[McpServerName.HELP_SCOUT],
       user_id="user123"
   )
   

   userId specifies whose connected accounts and data you are accessing in Klavis. It should be a unique id for yourself, your team, or your organization.

   API Reference

   Full Strata API endpoints

3. Authenticate

   Python

   import webbrowser
   
   # Open OAuth authorization page
   webbrowser.open(response.oauth_urls[McpServerName.HELP_SCOUT])
   

   Get your Help Scout API key from your Help Scout Developers .

   🎉 Your Help Scout MCP Server is ready! Once authentication is complete, you can use your MCP server URL with any MCP-compatible client.

UI

1. Open Dashboard

   Go to your Dashboard.

2. Choose Help Scout

   Select Help Scout from the list of available integrations.

3. Authenticate

   Complete the OAuth flow to connect your Help Scout account.

4. Use in your app

   Copy the MCP endpoint URL and add it to your MCP-supported client (Claude Desktop, Cursor, VS Code, etc.).

Open Source

1. Clone repository (for developers to build from source)

   git clone https://github.com/klavis-ai/klavis
   cd klavis/mcp_servers/help_scout
   
2. Run with Docker

   # Pull the Docker image
   docker pull ghcr.io/klavis-ai/help_scout-mcp-server:latest
   
   # Run with OAuth support (requires Klavis API key)
   docker run -p 5000:5000 \
     -e KLAVIS_API_KEY=$KLAVIS_API_KEY \
     ghcr.io/klavis-ai/help_scout-mcp-server:latest
   
   # Or run with manual API key
   docker run -p 5000:5000 \
     -e AUTH_DATA='{"access_token":"your_help_scout_api_key"}' \
     ghcr.io/klavis-ai/help_scout-mcp-server:latest
   
3. Configure MCP client

   {
     "mcpServers": {
       "help_scout": {
         "url": "http://localhost:5000/mcp/"
       }
     }
   }
   

Available Tools

With our progressive discovery approach, Klavis System is capable of enabling all tools for Help Scout. Please use the get_tools API for more details. If you find any tool that is missing, please reach out to [e-mail].

Next Steps

AI Platform Integrations

Integrate Klavis MCP Servers with leading AI platforms

Integrations

Explore available MCP servers

API Reference

REST endpoints and schemas

White-label Authentication

Customize OAuth flows with your own branding