Can I trigger auto-transcription for a video using the agent?

Yes! Use the `transcribe_video` tool with the Project ID. Your agent will trigger CaptionHub's AI engine to start transcribing the video content instantly.

How do I get the download link for finished subtitles?

Simply ask the agent to `export_captions` and provide the Project ID and the language code (e.g., 'fr' or 'es'). It will return the export URL for your finished caption set.

Does the integration allow approving captions via the workspace?

Yes. Use the `approve_captions` tool with the Project ID and Language. This will mark the specific caption set as approved in your CaptionHub workflow.

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

Name: CaptionHub
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Connect your CaptionHub account to any AI agent and orchestrate your video localization, AI-powered transcription, and subtitle approval workflows through natural conversation.

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

Project Oversight — List all localization projects and retrieve detailed metadata, including source and target languages.
Automated Transcription — Trigger AI-powered auto-transcription for your video assets directly from your workspace.
Caption Lifecycle — Handover, approve, or archive caption sets for specific languages using natural language.
Export Coordination — Retrieve export links for finished captions in various formats straight from your workspace.
Workflow Automation — Monitor active webhooks and project statuses to ensure your localization pipeline is efficient.
Data Deep Dives — Get detailed data for specific project, caption, or user IDs using natural language.

The CaptionHub 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 CaptionHub to CrewAI via MCP

Follow these steps to integrate the CaptionHub 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 CaptionHub

Why Use CrewAI with the CaptionHub MCP Server

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

CaptionHub + CrewAI Use Cases

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

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

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

CaptionHub MCP Tools for CrewAI (10)

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

approve_captions

Approve a caption set for a specific language

archive_project

Archive a project permanently

create_project

Create a new captioning project

export_captions

Get the export URL for a caption set

get_account_info

Retrieve core account information

get_project_details

Get details of a specific project

list_projects

List all video captioning projects

list_webhooks

List all active webhooks

transcribe_video

Trigger AI auto-transcription for a project

update_project

Update project metadata

Example Prompts for CaptionHub in CrewAI

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

"List all my current video projects in CaptionHub."

"Start auto-transcription for the 'Product Keynote' project."

"Get the French subtitle export link for project proj_123."

Troubleshooting CaptionHub MCP Server with CrewAI

Common issues when connecting CaptionHub 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.

CaptionHub + CrewAI FAQ

Common questions about integrating CaptionHub 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.