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Podcast Index MCP Server for Pydantic AIGive Pydantic AI instant access to 16 tools to Get Episode By Guid, Get Episodes By Feed Id, Get Episodes By Feed Url, and more

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Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Podcast Index through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Ask AI about this MCP Server for Pydantic AI

The Podcast Index MCP Server for Pydantic AI is a standout in the Audio Music category — giving your AI agent 16 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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python
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 Podcast Index "
            "(16 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Podcast Index?"
    )
    print(result.data)

asyncio.run(main())
Podcast Index
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* 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 Podcast Index MCP Server

Connect to the Podcast Index to tap into a massive, independent database of podcasts and episodes. This MCP server allows your AI agent to browse the open podcasting directory without the restrictions of proprietary platforms.

Pydantic AI validates every Podcast Index tool response against typed schemas, catching data inconsistencies at build time. Connect 16 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

  • Deep Search — Find podcasts by general terms, specific titles, or even by the people (hosts/guests) featured in them.
  • Metadata Retrieval — Fetch comprehensive details using RSS feed URLs, Index IDs, Podcast GUIDs, or iTunes IDs.
  • Episode Discovery — List all episodes for a specific feed or find individual episodes by their unique GUID.
  • Trending & Recent — Stay updated with recent feeds and episodes, or discover something new with random episode selection.

The Podcast Index MCP Server exposes 16 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 16 Podcast Index tools available for Pydantic AI

When Pydantic AI connects to Podcast Index through Vinkius, your AI agent gets direct access to every tool listed below — spanning podcasting, directory-api, metadata-retrieval, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get episode by guid on Podcast Index

Get a specific episode by its GUID

get

Get episodes by feed id on Podcast Index

List episodes for a specific feed ID

get

Get episodes by feed url on Podcast Index

List episodes for a specific feed URL

get

Get podcast by feed id on Podcast Index

Get podcast details using its internal Index ID

get

Get podcast by feed url on Podcast Index

Get podcast details using its RSS feed URL

get

Get podcast by guid on Podcast Index

Get podcast details using its Podcast GUID

get

Get podcast by itunes id on Podcast Index

Get podcast details using its iTunes ID

get

Get random episodes on Podcast Index

Get a selection of random episodes

get

Get recent episodes on Podcast Index

Get the most recently published episodes

get

Get recent feeds on Podcast Index

Get the most recently added or updated feeds

get

Get recent new feeds on Podcast Index

Get feeds newly added to the index

get

Get value by feed id on Podcast Index

Get the value block by feed ID

get

Get value by feed url on Podcast Index

Get the value block (e.g., Lightning Network details) for a feed URL

search

Search by person on Podcast Index

Search for podcasts featuring a specific person

search

Search by term on Podcast Index

Search for podcasts by a general search term

search

Search by title on Podcast Index

Search for podcasts by title

Connect Podcast Index to Pydantic AI via MCP

Follow these steps to wire Podcast Index into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 16 tools from Podcast Index with type-safe schemas

Why Use Pydantic AI with the Podcast Index MCP Server

Pydantic AI provides unique advantages when paired with Podcast Index through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Podcast Index integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your Podcast Index connection logic from agent behavior for testable, maintainable code

Podcast Index + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Podcast Index MCP Server delivers measurable value.

01

Type-safe data pipelines: query Podcast Index with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple Podcast Index tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query Podcast Index and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock Podcast Index responses and write comprehensive agent tests

Example Prompts for Podcast Index in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Podcast Index immediately.

01

"Search for podcasts about artificial intelligence using a general term."

02

"Find all podcasts featuring Lex Fridman."

03

"Get the latest episodes for the podcast with feed ID 750746."

Troubleshooting Podcast Index MCP Server with Pydantic AI

Common issues when connecting Podcast Index to Pydantic AI through Vinkius, and how to resolve them.

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Podcast Index + Pydantic AI FAQ

Common questions about integrating Podcast Index MCP Server with Pydantic AI.

01

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
02

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Podcast Index MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

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