Heroku Platform MCP Server

The Heroku Platform MCP Server is a purpose‑built Model Context Protocol (MCP) implementation that bridges large language models with the Heroku ecosystem. By exposing a rich set of tools, prompts, and resource interfaces, it lets AI assistants read, modify, and orchestrate Heroku applications, add-ons, pipelines, and more—all through natural language commands. This eliminates the need for developers to manually run CLI commands or craft API calls, streamlining workflows that involve deployment, scaling, monitoring, and troubleshooting.

At its core, the server leverages Heroku’s CLI authentication to provide secure, token‑based access. Once an authorization token is supplied, the MCP server translates LLM prompts into authenticated API calls against Heroku’s platform. The result is a seamless, conversational interface: an assistant can answer questions like “Show me the dyno usage for my app” or “Scale web to 5 instances,” and the server will return real‑time data or execute the requested change. This tight integration is valuable for developers who want to automate routine operations, generate deployment scripts on the fly, or embed platform management into larger AI‑powered workflows.

Key capabilities include:

• Resource discovery – list apps, add‑ons, pipelines, and environments.
• Lifecycle management – create, update, delete, or restart apps and dynos.
• Configuration handling – read and modify config vars, buildpacks, and stack settings.
• Add‑on orchestration – provision, bind, or detach add‑ons directly from the LLM.
• Monitoring and logs – fetch real‑time logs, metrics, and performance data.

These features are exposed through intuitive tool definitions that map directly to Heroku’s REST endpoints. Developers can extend or customize the server by adding new tools, but even the out‑of‑the‑box set is powerful enough to cover most day‑to‑day Heroku tasks.

Typical use cases span from rapid prototyping—where an AI assistant can spin up a temporary staging app—to continuous delivery pipelines, where the MCP server is invoked by CI/CD agents to trigger deployments or rollback on failure. It also shines in educational settings, allowing students to experiment with cloud deployment concepts without leaving the chat interface. Because the server operates on Heroku’s Common Runtime, Cedar Private and Shield Spaces, and Fir Private Spaces, it supports both public and highly secure environments.

Integration is straightforward: most MCP‑compatible tools (Claude Desktop, Zed, Cursor, Windsurf, Cline, VS Code) provide configuration snippets that point to the Heroku MCP server. Once configured, any AI workflow can call Heroku‑specific actions as if they were built‑in functions. This plug‑and‑play model removes friction, enabling developers to focus on higher‑level business logic while the server handles the plumbing of cloud operations.