Transistor MCP Server

Overview

The Transistor MCP Server bridges the gap between AI assistants and the Transistor.fm podcast platform, enabling developers to automate podcast management directly from conversational agents. By exposing a set of well‑structured tools, it allows Claude or other MCP‑enabled assistants to authenticate with Transistor, retrieve show and episode data, upload new audio files, and pull detailed analytics—all through simple JSON requests. This eliminates the need for manual API calls or custom integrations, making it easier to embed podcast workflows into broader AI‑driven applications.

What Problem It Solves

Podcast creators often juggle multiple platforms: hosting, distribution, analytics, and content management. Without a unified interface, developers must write separate scripts for each Transistor API endpoint, handle authentication tokens, and parse complex responses. The Transistor MCP Server consolidates these interactions into a single, reusable service that follows the MCP specification. This means AI assistants can perform tasks like “create a new episode with this transcript” or “list my latest shows” without any manual coding, streamlining content production and data retrieval.

Core Capabilities

• Authentication & User Info – returns account details, confirming the API key’s validity and providing context for subsequent actions.
• File Upload Workflow – supplies a pre‑signed S3 URL and content type, simplifying the two‑step process of uploading audio before episode creation.
• Show & Episode Management – , , and let assistants enumerate, filter, and publish content programmatically. Pagination, status filters, and ordering options make large libraries manageable.
• Rich Episode Retrieval – supports sparse fieldsets and related resources, enabling assistants to fetch only the data they need for a given task.
• Analytics Access – delivers listen counts, downloads, and engagement metrics over custom date ranges, allowing data‑driven decision making within the AI workflow.

Real‑World Use Cases

• Automated Publishing Pipelines – A content creator can ask the AI to “publish this new episode with the provided transcript and artwork,” and the assistant will handle uploading, metadata attachment, and scheduling.
• Data‑Driven Insights – Marketing teams can request “show me the top 5 episodes by downloads in the last month,” and receive concise analytics that can be fed into dashboards or reporting tools.
• Content Planning – By combining and , a planner can generate episode calendars, detect gaps in season numbering, or flag overdue uploads.
• Interactive Q&A – Podcast hosts can integrate the server into chatbots that answer listener questions about episode availability, release dates, or show details on demand.

Integration with AI Workflows

The server’s tools fit naturally into MCP‑based workflows. A developer can configure the MCP client to point at this server, then invoke tools via simple JSON payloads. Because each tool follows a predictable request/response contract, AI assistants can reason about the next step—e.g., after obtaining an upload URL, they can automatically transfer the file and then call . This composability enables complex, multi‑step operations to be expressed as conversational prompts, greatly reducing friction for non‑technical users.

Unique Advantages

• End‑to‑end Automation – From authentication to publishing, all steps are covered without leaving the MCP ecosystem.
• Simplified File Handling – The pre‑signed URL mechanism abstracts away AWS S3 intricacies, letting AI assistants focus on content rather than infrastructure.
• Rich Metadata Support – The tool accepts a wide array of optional fields (transcripts, keywords, video links), giving creators full control over episode presentation.
• Analytics Integration – Direct access to Transistor’s metrics allows developers to build data‑centric applications, such as recommendation engines or trend analysis dashboards.

In summary, the Transistor MCP Server equips AI assistants with a powerful, single point of contact to manage podcast content and analytics. By streamlining authentication, file uploads, episode creation, and data retrieval, it empowers developers to build sophisticated, conversational podcast workflows that save time, reduce errors, and unlock new possibilities for content creators.