Hiro.fm MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Add Audio, Create Contact, Get Contact, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Hiro.fm as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Hiro.fm app connector for LlamaIndex is a standout in the Marketing Automation category — giving your AI agent 10 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Hiro.fm. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Hiro.fm?"
)
print(response)
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 Hiro.fm MCP Server
Connect your Hiro.fm creator account to any AI agent and take full control of your private podcasting workflows through natural conversation.
LlamaIndex agents combine Hiro.fm tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Listener Management — Create new contacts and manage your listener database with direct access to profiles and metadata
- Access Control — Programmatically grant or revoke access to specific private shows for any contact in your database
- Content Automation — Add new audio episodes to your shows by providing titles and direct media URLs directly through your agent
- Show Monitoring — List all your private podcast shows and retrieve detailed metadata including subscriber counts and IDs
- Tagging & Segmentation — Manage contact tags to organize your audience for targeted content delivery and automation
The Hiro.fm MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 10 Hiro.fm tools available for LlamaIndex
When LlamaIndex connects to Hiro.fm through Vinkius, your AI agent gets direct access to every tool listed below — spanning podcasting, audio-content, creator-economy, 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 new audio episode
Create a new contact
Get contact details
Get show details
Grant access to a show
List audio episodes for a show
fm account. List all contacts (listeners)
List all podcast shows
List all contact tags
Revoke access from a show
Connect Hiro.fm to LlamaIndex via MCP
Follow these steps to wire Hiro.fm into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Hiro.fm MCP Server
LlamaIndex provides unique advantages when paired with Hiro.fm through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Hiro.fm tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Hiro.fm tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Hiro.fm, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Hiro.fm tools were called, what data was returned, and how it influenced the final answer
Hiro.fm + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Hiro.fm MCP Server delivers measurable value.
Hybrid search: combine Hiro.fm real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Hiro.fm to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Hiro.fm for fresh data
Analytical workflows: chain Hiro.fm queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Hiro.fm in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Hiro.fm immediately.
"List all my podcast shows from Hiro.fm."
"Grant listener access for 'john@example.com' to the 'Elite Coaching' show."
"Add a new episode titled 'Welcome Session' to my show ID 'sh_1'."
Troubleshooting Hiro.fm MCP Server with LlamaIndex
Common issues when connecting Hiro.fm to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHiro.fm + LlamaIndex FAQ
Common questions about integrating Hiro.fm MCP Server with LlamaIndex.