Transistor MCP Server

Created By
gxjansena year ago
Transistor MCP server implementation for use with your LLM
Overview

What is Transistor MCP Server?

Transistor MCP Server is a server implementation designed to interact with the Transistor.fm API, enabling users to manage podcasts, episodes, and view analytics.

How to use Transistor MCP Server?

To use the Transistor MCP Server, you need to add it to your MCP settings configuration file with your Transistor API key and then utilize the available tools to manage your podcast content.

Key features of Transistor MCP Server?

  • Get details of the authenticated user account.
  • Authorize uploads of audio files with pre-signed URLs.
  • List all shows and episodes in your Transistor.fm account.
  • Create and update episodes with various metadata options.
  • Retrieve analytics for shows and episodes.
  • Manage webhooks for real-time updates.

Use cases of Transistor MCP Server?

  1. Managing podcast episodes and shows efficiently.
  2. Analyzing podcast performance through detailed analytics.
  3. Automating audio file uploads and episode creation.
  4. Integrating with other services via webhooks for real-time notifications.

FAQ from Transistor MCP Server?

  • Can I manage multiple podcasts with this server?

Yes! You can manage multiple shows and episodes through the Transistor MCP Server.

  • Is there a limit on API requests?

Yes, API requests are rate-limited to 10 requests per 10 seconds.

  • What programming languages can I use with this server?

The server can be used with any programming language that can make HTTP requests, but examples are provided in JavaScript.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
gxjansen
Star
-
Language
-
License
-

Recommend Servers

View All
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago