Can I filter searches by audio length?

The current tools support text queries and basic sorting. For advanced filtering like audio length, you can append parameters to the search string or use specific episode details tools.

How do I find the ID of a specific genre?

Use the `list_podcast_genres` tool. It returns a full mapping of genre names to their unique numerical IDs.

Does this server provide audio download links?

Yes, the `get_episode_details` tool retrieves the metadata including available audio stream URLs and the official website links.

Listen Notes MCP Server for CrewAI 7 tools — connect in under 2 minutes

Name: Listen Notes
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 7 Tools Framework

Connect your CrewAI agents to Listen Notes through Vinkius, pass the Edge URL in the `mcps` parameter and every Listen Notes tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Listen Notes Specialist",
    goal="Help users interact with Listen Notes effectively",
    backstory=(
        "You are an expert at leveraging Listen Notes tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Listen Notes "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 7 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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 Listen Notes MCP Server

Connect the Listen Notes Podcast API to any AI agent to automate your podcast discovery and research workflows. This MCP server enables your agent to search for specific episodes, retrieve complete podcast metadata, explore trending topics, and access curated lists directly from natural language interfaces.

When paired with CrewAI, Listen Notes becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Listen Notes tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Global Podcast Search — Search for podcasts or individual episodes across the entire database using keywords
Episode Insights — Retrieve complete metadata for any episode, including descriptions, audio links, and transcripts (if available)
Discovery & Curation — Explore best podcasts by genre, access expert-curated lists, and monitor trending search terms
Podcast Database Access — Fetch full show details, publisher information, and chronological episode lists
Genre Exploration — List and query specific categories to identify niche podcast communities

The Listen Notes MCP Server exposes 7 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Listen Notes to CrewAI via MCP

Follow these steps to integrate the Listen Notes MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 7 tools from Listen Notes

Why Use CrewAI with the Listen Notes MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Listen Notes through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Listen Notes + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Listen Notes MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Listen Notes for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Listen Notes, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Listen Notes tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Listen Notes against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Listen Notes MCP Tools for CrewAI (7)

These 7 tools become available when you connect Listen Notes to CrewAI via MCP:

get_best_podcasts

You can provide an optional genre_id. Get a list of best podcasts by genre

get_curated_podcasts

Get lists of curated podcasts

get_episode_details

Get metadata for a specific podcast episode

get_podcast_details

Get complete metadata and episodes for a podcast

get_trending_podcast_searches

Get the most recent trending search terms

list_podcast_genres

List all available podcast genres

search_podcasts_or_episodes

Use the "q" parameter for your query. Search for podcasts or individual episodes

Example Prompts for Listen Notes in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Listen Notes immediately.

"Search for podcast episodes about 'Quantum Computing'."

"What are the trending searches on Listen Notes right now?"

"Get details for the podcast with ID '987654321'."

Troubleshooting Listen Notes MCP Server with CrewAI

Common issues when connecting Listen Notes to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Listen Notes + CrewAI FAQ

Common questions about integrating Listen Notes MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.