Can I get direct download links for my videos through the agent?

Yes. The `get_video_source_files` tool allows your agent to retrieve direct MP4 download links and stream URLs for different qualities (like 720p or 1080p), making it easy to share raw files or use them in other applications.

How do I add a video to a specific player?

Use the `attach_video_to_player` tool. You'll need to provide the `player_id` and the `video_id`. Your agent can help you find these IDs by listing your players and videos first.

Can I create new video players through conversation?

Absolutely. The `create_empty_player` tool lets you provision a new player container with a descriptive name. Once created, you can attach videos to it and manage its settings directly through your agent.

Vidyard MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Vidyard
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Vidyard through Vinkius, pass the Edge URL in the `mcps` parameter and every Vidyard 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

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Vidyard Specialist",
    goal="Help users interact with Vidyard effectively",
    backstory=(
        "You are an expert at leveraging Vidyard 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 Vidyard "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Vidyard MCP Server

Connect your Vidyard account to any AI agent and manage your business video library through natural conversation.

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

Video Library — List all video assets stored in your Vidyard dashboard and retrieve unique video IDs
Metadata & Details — Get technical metadata for any video including length, encoding status, and descriptions
Player Management — Create, update, and manage video players (facades) to customize how your content is embedded
Video Organization — Attach videos to specific players and organize your content for different marketing or sales needs
Direct Stream Access — Retrieve direct stream URLs and raw MP4 download links for various video qualities (480p, 720p, etc.)
Asset Management — Rename players or permanently delete video assets and player containers from your dashboard

The Vidyard MCP Server exposes 10 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 Vidyard to CrewAI via MCP

Follow these steps to integrate the Vidyard 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 10 tools from Vidyard

Why Use CrewAI with the Vidyard MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Vidyard 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

Vidyard + CrewAI Use Cases

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

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

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

Vidyard MCP Tools for CrewAI (10)

These 10 tools become available when you connect Vidyard to CrewAI via MCP:

attach_video_to_player

Requires both player ID and video ID. Adds a video asset into a specific player container

create_empty_player

Creates a new, empty video player container

delete_video_asset

This action is irreversible. Permanently deletes a video asset from Vidyard

delete_video_player

Note that the original video assets are not deleted. Permanently deletes a video player

get_player_details

Retrieves details for a specific video player

get_video_details

Retrieves technical metadata for a specific video asset

get_video_source_files

Retrieves direct stream URLs for various video qualities (480p, 720p, etc.)

list_video_players

Lists all configured video players (facades) in the account

list_videos

Lists all video assets stored in the Vidyard dashboard

update_player_name

Updates the display name or title of an existing player

Example Prompts for Vidyard in CrewAI

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

"List all my videos in Vidyard."

"Get the direct download links for the 'Product Demo' video."

"Create a new player called 'Website Homepage' and attach my latest video to it."

Troubleshooting Vidyard MCP Server with CrewAI

Common issues when connecting Vidyard 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.

Vidyard + CrewAI FAQ

Common questions about integrating Vidyard 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.