Can I see the AI-generated notes for a specific meeting?

Yes! Use the `get_meeting_notes` tool and provide the Meeting ID. Your agent will retrieve the complete AI summary and key points recorded for that session.

How do I search for a specific discussion point in the transcript?

Run the `get_meeting_transcript` query with the Meeting ID. The agent will retrieve the full text, allowing you to ask the AI to find or summarize specific parts of the conversation.

Is it possible to list the participants of a meeting via AI?

Absolutely. Use the `get_meeting_participants` tool and provide the Meeting ID. The agent will return the directory of everyone who attended the recorded session.

INSTANT PLUG AND PLAY

tl;dv MCP Server for CrewAIGive CrewAI instant access to 12 tools to Get Api Status, Get Meeting Details, Get Meeting Duration, and more

Name: tl;dv
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 12 Tools Framework

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

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The tl;dv app connector for CrewAI is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="tl;dv Specialist",
    goal="Help users interact with tl;dv effectively",
    backstory=(
        "You are an expert at leveraging tl;dv 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 tl;dv "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 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 tl;dv MCP Server

Connect your tl;dv account to any AI agent and simplify how you manage your meeting recordings, transcripts, and AI-generated insights through natural conversation.

When paired with CrewAI, tl;dv becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call tl;dv 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

Meeting Oversight — List all recorded meetings and retrieve detailed metadata, including participants and duration.
Transcript Access — Fetch full transcriptions for any meeting to search for specific discussion points.
AI Insights — Read AI-generated notes, summaries, and key moments (highlights) to quickly understand meeting outcomes.
External Import — Programmatically import meeting recordings from external URLs for processing.
Content Retrieval — Get direct download links for video recordings and access recent transcripts instantly.
Operational Monitoring — Check API connectivity and account status directly from the agent.

The tl;dv MCP Server exposes 12 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.

All 12 tl;dv tools available for CrewAI

When CrewAI connects to tl;dv through Vinkius, your AI agent gets direct access to every tool listed below — spanning meeting-transcription, call-recording, summarization, 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.

get_api_status

Check connection

get_meeting_details

Get meeting info

get_meeting_duration

Check call length

get_meeting_highlights

Get key moments

get_meeting_notes

Read AI summaries

get_meeting_participants

List attendees

get_meeting_transcript

Read transcription

get_recording_download

Get video file URL

import_external_meeting

Upload recording URL

list_recent_transcripts

List latest transcripts

list_recorded_meetings

List recent meetings

test_tldv_auth

Verify credentials

Connect tl;dv to CrewAI via MCP

Follow these steps to wire tl;dv into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

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 12 tools from tl;dv

Why Use CrewAI with the tl;dv MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with tl;dv 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

tl;dv + CrewAI Use Cases

Practical scenarios where CrewAI combined with the tl;dv MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries tl;dv 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 tl;dv, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain tl;dv 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 tl;dv against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for tl;dv in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with tl;dv immediately.

"List all my recorded meetings from this month."

"Summarize the key decisions made in the 'Q4 Roadmap Sync' meeting."

"Show me who attended the meeting with 'Alex' (ID: mtg_88231)."

Troubleshooting tl;dv MCP Server with CrewAI

Common issues when connecting tl;dv 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.

tl;dv + CrewAI FAQ

Common questions about integrating tl;dv 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.