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api.video MCP Server for CrewAIGive CrewAI instant access to 9 tools to Create Video Object, Delete Video, Get Video Analytics, and more

Built by Vinkius GDPR 9 Tools Framework

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

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The api.video app connector for CrewAI is a standout in the Developer Tools category — giving your AI agent 9 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="api.video Specialist",
    goal="Help users interact with api.video effectively",
    backstory=(
        "You are an expert at leveraging api.video 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 api.video "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 9 available tools "
        "and what they can do."
    ),
)

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

Connect your api.video account to any AI agent and take full control of your professional video hosting infrastructure and automated media workflows through natural conversation.

When paired with CrewAI, api.video becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call api.video 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 Orchestration — List and manage your entire high-fidelity video library programmatically, or create new video objects to prepare for uploads in real-time
  • Asset Intelligence — Retrieve detailed high-fidelity status and direct asset URLs for players, thumbnails, and navigation markers (chapters) directly through your agent
  • Deep Analytics Tracking — Monitor performance metrics like total plays and impressions using high-fidelity aggregation tools to coordinate your content strategy
  • Multilingual Captions — Access and manage subtitle tracks across multiple languages to maintain a perfectly coordinated global viewer experience
  • Infrastructure Monitoring — Access your directory of custom player themes and store-level metadata directly through your agent for instant operational reporting

The api.video MCP Server exposes 9 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 9 api.video tools available for CrewAI

When CrewAI connects to api.video through Vinkius, your AI agent gets direct access to every tool listed below — spanning video-hosting, video-streaming, encoding, 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.

create_video_object

Set title and description here. Initialize a new video

delete_video

video. Permanently delete a video

get_video_analytics

Retrieve performance metrics

get_video_details

Get metadata for a video

list_player_themes

List custom player themes

list_video_captions

List captions for a video

list_video_chapters

List chapters for a video

list_videos

Supports filtering by title or tags. List your api.video videos

update_video_details

Modify video metadata

Connect api.video to CrewAI via MCP

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

01

Install CrewAI

Run pip install crewai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
03

Customize the agent

Adjust the role, goal, and backstory to fit your use case
04

Run the crew

Run python crew.py. CrewAI auto-discovers 9 tools from api.video

Why Use CrewAI with the api.video MCP Server

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

01

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

02

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

03

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

04

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

api.video + CrewAI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for api.video in CrewAI

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

01

"List the last 5 videos in my api.video account."

02

"Show the play count analytics for all videos this month."

03

"Get the player link and captions for video ID 'vi123'."

Troubleshooting api.video MCP Server with CrewAI

Common issues when connecting api.video to CrewAI through the Vinkius, and how to resolve them.

01

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
02

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
03

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
04

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.

api.video + CrewAI FAQ

Common questions about integrating api.video MCP Server with CrewAI.

01

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.
02

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.
03

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.
04

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.
05

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.