Transistor.fm MCP Server for Pydantic AIGive Pydantic AI instant access to 11 tools to Add Subscriber, Create Episode, Delete Episode, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Transistor.fm through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The Transistor.fm app connector for Pydantic AI is a standout in the Marketing Automation category — giving your AI agent 11 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Transistor.fm "
"(11 tools)."
),
)
result = await agent.run(
"What tools are available in Transistor.fm?"
)
print(result.data)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Transistor.fm MCP Server
Connect your Transistor.fm podcasting account to any AI agent and simplify how you manage your shows, publish new episodes, and grow your audience through natural conversation.
Pydantic AI validates every Transistor.fm tool response against typed schemas, catching data inconsistencies at build time. Connect 11 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- Show Management — List all your podcast shows and retrieve detailed metadata, RSS feeds, and configurations.
- Episode Workflow — Create, update, and publish podcast episodes with full control over titles, descriptions, and show notes.
- Content Curation — List and search through your entire episode library for any show to manage your publishing history.
- Private Podcasting — Manage subscribers for your private shows, including adding new email-based members programmatically.
- Lifecycle Control — Delete unwanted episodes or drafts to keep your podcast feed organized.
- Account Visibility — Fetch your profile details and verify account settings directly from the agent.
The Transistor.fm MCP Server exposes 11 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 11 Transistor.fm tools available for Pydantic AI
When Pydantic AI connects to Transistor.fm through Vinkius, your AI agent gets direct access to every tool listed below — spanning podcast-hosting, rss-feeds, podcast-analytics, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Add a subscriber to a private podcast
Create a new episode
Delete an episode
fm account. Get account details
Get details for an episode
Get details for a specific show
List episodes for a show
List all podcast shows
List private podcast subscribers
Publish an episode
Update an existing episode
Connect Transistor.fm to Pydantic AI via MCP
Follow these steps to wire Transistor.fm into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Transistor.fm MCP Server
Pydantic AI provides unique advantages when paired with Transistor.fm through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Transistor.fm integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Transistor.fm connection logic from agent behavior for testable, maintainable code
Transistor.fm + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Transistor.fm MCP Server delivers measurable value.
Type-safe data pipelines: query Transistor.fm with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Transistor.fm tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Transistor.fm and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Transistor.fm responses and write comprehensive agent tests
Example Prompts for Transistor.fm in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Transistor.fm immediately.
"List all my podcast shows in Transistor.fm."
"Show me the last 3 episodes for 'The AI Revolution'."
"Add 'jane.doe@example.com' as a subscriber to show 'show_10293'."
Troubleshooting Transistor.fm MCP Server with Pydantic AI
Common issues when connecting Transistor.fm to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiTransistor.fm + Pydantic AI FAQ
Common questions about integrating Transistor.fm MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.