Heroku MCP Server
Check Heroku app dyno health, manage configurations, and trigger direct git deployments through Model Context Protocol.
Quick Answer / TL;DR
The Heroku MCP server establishes a secure, local or remote JSON-RPC 2.0 communication tunnel, allowing AI models (like Claude or Cursor) to automatically discover and execute capabilities (tools, prompts, and resources) within the Heroku ecosystem with extremely low latency.
Key Takeaways
- Restart web dynos during heavy loads
- Retrieve configuration variables
- Stream live server errors
Core Integration Concept
Connecting the model to Heroku bypasses complex setup. The LLM can auto-discover what endpoints are active, what input variables are expected, and how answers will be delivered.
Verified Use Cases
Setup Overview
Connection Setup Checklist
- Prepare Credentials: Obtain your Heroku API Key credentials directly from your Heroku settings.
- Update Config: Add the executable tool command structure directly to your Claude config file.
- Restart & Confirm: Reload the desktop model client to complete the connection handshake sequence.
Sample Connection Schema
{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "execute_heroku",
"arguments": {
"query": "status_check"
}
},
"id": 1
}Security Considerations
To guarantee perfect data isolation, safeguard the Heroku API Key credentials. Always run integrations in sandboxed contexts to block unsolicited access.
Best Practices
- Configure exact resource boundaries for the Dyno restarts feature.
- Configure exact resource boundaries for the Log streaming feature.
- Configure exact resource boundaries for the Config management feature.
- Configure exact resource boundaries for the App metric reports feature.
Required Auth Keys
Heroku API Key
Deploy Heroku Server
Deploy this Heroku integration to our global edge container cluster. Zero DevOps, instant SSE.
Related Connectors
Heroku - FAQ
Contextual information and technical support details regarding Model Context Protocol integration