Heroku MCP Server

What does “Heroku” MCP Server do?

The Heroku MCP Server is a Model Context Protocol (MCP) server that integrates with the Heroku platform using the Heroku CLI. It acts as a bridge between AI assistants and the Heroku platform, enabling seamless access to Heroku resources and automation of platform tasks through standardized MCP tools and interfaces. This server empowers AI-driven workflows to interact programmatically with Heroku apps, deployments, and configurations—enabling tasks such as querying app status, managing resources, and automating deployment processes. By exposing Heroku operations to LLMs, developers can streamline their development, deployment, and management workflows, making Heroku’s cloud platform services more accessible and programmable through modern AI development environments.

List of Prompts

No prompt templates are mentioned in the available documentation or source files.

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List of Resources

No explicit MCP resources are documented or listed in the available repository files.

List of Tools

No detailed list of tools is explicitly documented in the available repository files. However, as a Heroku MCP server, it can be reasonably inferred that it exposes Heroku CLI functionalities as tools (e.g., deploy app, list apps, manage configs), but no explicit tool descriptions are found in the available files.

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Use Cases of this MCP Server

• Heroku Application Management
  Enables developers to manage Heroku applications directly from AI-powered development environments, streamlining tasks such as app creation, scaling, and deletion.

• Automated Deployments
  Facilitates the automation of deployment workflows, allowing LLMs to trigger deployments, rollbacks, or releases through Heroku CLI commands.

• Resource Monitoring
  Allows AI agents to monitor app status, retrieve logs, and get performance metrics from Heroku apps, enabling proactive maintenance and troubleshooting.

• Configuration Management
  Supports the management of environment variables and configuration settings for Heroku apps, improving the speed and reliability of app configuration changes.

How to set it up

Windsurf

1. Ensure you have Node.js installed.
2. Open your Windsurf configuration file.
3. Add the Heroku MCP Server to the mcpServers object, using the following JSON snippet:

   {
     "heroku": {
       "command": "npx",
       "args": ["-y", "@heroku/mcp-server@latest"]
     }
   }
   

4. Save the configuration and restart Windsurf.
5. Verify that the Heroku MCP Server is running and accessible.

Securing API Keys

{
  "heroku": {
    "command": "npx",
    "args": ["-y", "@heroku/mcp-server@latest"],
    "env": {
      "HEROKU_API_KEY": "<YOUR_HEROKU_API_KEY>"
    }
  }
}

Claude

1. Ensure Node.js is installed.
2. Open Claude MCP configuration.
3. Add the Heroku MCP Server using:

   {
     "heroku": {
       "command": "npx",
       "args": ["-y", "@heroku/mcp-server@latest"]
     }
   }
   

4. Save changes and restart Claude.
5. Confirm server connectivity.

Securing API Keys

{
  "heroku": {
    "command": "npx",
    "args": ["-y", "@heroku/mcp-server@latest"],
    "env": {
      "HEROKU_API_KEY": "<YOUR_HEROKU_API_KEY>"
    }
  }
}

Cursor

1. Make sure Node.js is installed.
2. Open your Cursor settings.
3. Add the Heroku MCP Server under mcpServers:

   {
     "heroku": {
       "command": "npx",
       "args": ["-y", "@heroku/mcp-server@latest"]
     }
   }
   

4. Save and restart Cursor.
5. Check that the MCP server is registered.

Securing API Keys

{
  "heroku": {
    "command": "npx",
    "args": ["-y", "@heroku/mcp-server@latest"],
    "env": {
      "HEROKU_API_KEY": "<YOUR_HEROKU_API_KEY>"
    }
  }
}

Cline

1. Confirm Node.js installation.
2. Open the Cline configuration file.
3. Add the Heroku MCP Server configuration:

   {
     "heroku": {
       "command": "npx",
       "args": ["-y", "@heroku/mcp-server@latest"]
     }
   }
   

4. Save your changes and restart Cline.
5. Ensure the Heroku MCP Server is active.

Securing API Keys

{
  "heroku": {
    "command": "npx",
    "args": ["-y", "@heroku/mcp-server@latest"],
    "env": {
      "HEROKU_API_KEY": "<YOUR_HEROKU_API_KEY>"
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "heroku": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “heroku” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the above, the Heroku MCP Server provides a basic MCP integration for Heroku but lacks detailed documentation of prompts, tools, or resources. The presence of a LICENSE and setup instructions is a positive, but the lack of specific MCP features reduces its utility score.

Our opinion

This MCP server has value for Heroku users wanting to automate and manage cloud apps via MCP, but documentation is sparse, and key MCP elements (tools, prompts, resources) are missing or undocumented. Given this, the score would be moderate for utility and completeness.

MCP Score