Podbean MCP Server

Podbean MCP Server

The Podbean MCP server bridges the gap between conversational AI assistants and the Podbean podcast platform. By exposing a well‑defined set of resources, tools, prompts, and sampling endpoints, it allows developers to control podcasts—creating, updating, publishing episodes, and harvesting analytics—all through natural language interactions with Claude or any MCP‑compatible client. This eliminates the need for manual API calls, enabling a truly conversational workflow where podcast managers can ask an assistant to “publish the latest episode” or “show me my download stats for March.”

At its core, the server implements client‑credentials authentication for a user’s own podcasts and an optional OAuth flow for third‑party access. It maintains token state, letting developers juggle multiple podcasts without switching contexts. Once authenticated, the server offers a suite of podcast‑management capabilities: listing all owned shows, retrieving detailed metadata, browsing categories, and accessing public oEmbed data for any episode. Episode management is equally comprehensive—listing episodes, inspecting individual details, publishing new content with a single command, updating metadata on the fly, and deleting out‑of‑sync releases. The file‑management endpoint supplies presigned URLs for uploading audio files, though actual uploads must be handled externally due to STDIO protocol limits.

Analytics integration is a standout feature. The server exposes download counts, daily listener totals, and interaction metrics, allowing an assistant to generate growth reports or alert the host when a new episode spikes in popularity. Developers can embed these analytics calls into larger workflows, such as automated email digests or Slack notifications triggered by threshold conditions.

Integrating the Podbean MCP into an AI workflow is straightforward. Once the server is running, a client can query resources like or invoke tools such as . Prompt templates guide the assistant to ask clarifying questions (e.g., “Which podcast should I publish to?”) before executing an action, ensuring safe and intentional interactions. Because the server adheres to MCP standards, any future AI client—whether a web IDE, desktop assistant, or custom chatbot—can consume its capabilities without bespoke adapters.

In summary, the Podbean MCP server empowers developers to treat podcast management as a conversational service. It centralizes authentication, streamlines episode lifecycle operations, delivers real‑time analytics, and supports public data access—all within the familiar MCP ecosystem. This makes it an invaluable component for creators who want to automate routine tasks, monitor audience engagement, and focus more on content than on repetitive administrative chores.