How do I start a new transcription?

Use the `create_job` tool and provide the public URL of your audio or video file. Your agent will initiate the process and provide a Job ID.

Can I check if a transcription is finished?

Yes. Use the `get_job` tool with the Job ID. It will return the current status and, if completed, the transcribed text.

How can I clean up my transcription history?

Use the `delete_job` tool and provide the Job ID. This permanently removes the transcription data from your 3Scribe account.

3Scribe MCP Server for CrewAI 4 tools — connect in under 2 minutes

Name: 3Scribe
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 4 Tools Framework

Connect your CrewAI agents to 3Scribe through Vinkius, pass the Edge URL in the `mcps` parameter and every 3Scribe 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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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="3Scribe Specialist",
    goal="Help users interact with 3Scribe effectively",
    backstory=(
        "You are an expert at leveraging 3Scribe 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 3Scribe "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 4 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 3Scribe MCP Server

Unlock the power of spoken word with 3Scribe, your automated partner for high-precision audio and video transcription. By connecting 3Scribe to your AI agent, you eliminate the friction of manual data entry from media files. Your agent can now orchestrate the entire transcription lifecycle—from submitting public URLs to auditing job statuses and retrieving final text—all through simple natural language commands. Whether it’s meeting minutes or video captions, your agent acts as a direct bridge to 3Scribe's powerful recognition engine.

When paired with CrewAI, 3Scribe becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call 3Scribe 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

Automated Transcription — Create new transcription jobs by providing a public URL to your audio or video files
Job Monitoring — Track the status of your transcriptions in real-time (Requested, Processing, Completed, Error)
Text Retrieval — Access raw text transcripts or detailed word-level data with timestamps and speaker IDs
Project Management — List all transcription jobs, filter by status, and delete old or unnecessary projects
Language Detection — Specify transcription languages or let the AI auto-detect the spoken language

The 3Scribe MCP Server exposes 4 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 3Scribe to CrewAI via MCP

Follow these steps to integrate the 3Scribe 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 4 tools from 3Scribe

Why Use CrewAI with the 3Scribe MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with 3Scribe 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

3Scribe + CrewAI Use Cases

Practical scenarios where CrewAI combined with the 3Scribe MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries 3Scribe 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 3Scribe, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain 3Scribe 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 3Scribe against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

3Scribe MCP Tools for CrewAI (4)

These 4 tools become available when you connect 3Scribe to CrewAI via MCP:

create_job

You must provide a valid public URL. Returns a Job ID useful for tracking progress. Initiate a new audio or video transcription job in 3Scribe via a public media URL

delete_job

This is an irreversible destructive action. Requires the Job ID. Permanently delete a transcription task and its associated data from the 3Scribe account

get_job

You must provide the Job ID. Check the status and retrieve the generated text of a specific 3Scribe transcription job

list_jobs

Retrieve a paginated list of all transcription tasks from the 3Scribe account

Example Prompts for 3Scribe in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with 3Scribe immediately.

"Transcribe the audio from this URL: https://example.com/podcast.mp3"

"What is the status of my transcription job 54321?"

"Delete my old transcription job with ID 99999."

Troubleshooting 3Scribe MCP Server with CrewAI

Common issues when connecting 3Scribe 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.

3Scribe + CrewAI FAQ

Common questions about integrating 3Scribe 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.