How do I get an Access Token for Frame.io?

You can generate a Personal Access Token in the Frame.io Developer Portal at https://developer.frame.io.

Can I add comments with a specific timecode using the agent?

Yes! The 'add_comment' tool accepts an optional 'timestamp' parameter in seconds, allowing you to pin your feedback to a specific moment in the video.

How do I see the assets inside a specific folder?

Use the 'list_assets' tool and provide the Folder ID as the 'parentId'. The agent will return all files and sub-folders contained within that directory.

Is it possible to list external review links?

Yes! Use the 'list_review_links' tool and provide the Project ID. The agent will retrieve all active shared links for that project.

Frame.io MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Frame.io
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Frame.io through Vinkius, pass the Edge URL in the `mcps` parameter and every Frame.io 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="Frame.io Specialist",
    goal="Help users interact with Frame.io effectively",
    backstory=(
        "You are an expert at leveraging Frame.io 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 Frame.io "
        "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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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 Frame.io MCP Server

Connect your Frame.io account to any AI agent to automate your video collaboration and creative workflows through the Model Context Protocol (MCP). Frame.io is the industry-leading platform for reviewing and approving media, allowing teams to stay in sync from anywhere in the world. This MCP server enables you to manage your projects, retrieve asset metadata, and participate in time-coded discussions directly through natural conversation.

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

Key Features

Project Oversight — List all projects within your teams and fetch detailed metadata including ownership and status.
Asset Management — List files and folders within projects and retrieve complete metadata for specific media assets.
Collaborative Feedback — List all comments on an asset and add new time-coded feedback directly from your chat interface.
Review Coordination — Access and list review links to monitor how your media is being shared with external stakeholders.
Team Interaction — List team members and collaborators to maintain full context of who is involved in each project.
Directory Structure — Navigate through folders and sub-folders within your project library to organize your work effectively.
Real-time Monitoring — Fetch specific asset details or comments to keep your post-production workflow moving fast.

The Frame.io 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.

How to Connect Frame.io to CrewAI via MCP

Follow these steps to integrate the Frame.io 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 12 tools from Frame.io

Why Use CrewAI with the Frame.io MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Frame.io 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

Frame.io + CrewAI Use Cases

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

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

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

Frame.io MCP Tools for CrewAI (12)

These 12 tools become available when you connect Frame.io to CrewAI via MCP:

add_comment

Post a new comment

get_asset_details

Get asset metadata

get_my_profile

Get current user profile

get_project_details

Get project metadata

list_accounts

List billing accounts

list_asset_comments

List comments on an asset

list_assets

List assets or folder contents

list_collaborators

List project collaborators

list_folders

List folders in project

list_projects

List projects in a team

list_review_links

List project review links

list_teams

List Frame.io teams

Example Prompts for Frame.io in CrewAI

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

"List all my projects in Frame.io team 'team_abc123'."

"Show me the last 5 comments on video asset 'vid_9876'."

"Add a comment to 'vid_9876': 'Great work, let\'s proceed to export' at 120 seconds."

Troubleshooting Frame.io MCP Server with CrewAI

Common issues when connecting Frame.io 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.

Frame.io + CrewAI FAQ

Common questions about integrating Frame.io 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.