Where do I find my Collect API key?

In the Collect dashboard, go to **Settings > Integrations > API** and generate a key. Copy it and paste it below.

Which authentication method does this use?

This integration uses Basic Authentication with your API Key as the password.

Can I export requests as PDF?

The API supports PDF exports. While this integration focuses on data management, you can retrieve the metadata needed to trigger an export.

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

Name: Collect
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Connect your AI to Collect, the secure platform for gathering information and documents from clients.

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

Campaign Management — List active data collection campaigns and check their completion status.
Request Sending — Send new data requests to clients by email for KYC, onboarding, or compliance workflows.
Status Tracking — Check the status of individual requests, view messages, and monitor completion.

The Collect 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 Collect to CrewAI via MCP

Follow these steps to integrate the Collect 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 Collect

Why Use CrewAI with the Collect MCP Server

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

Collect + CrewAI Use Cases

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

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

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

Collect MCP Tools for CrewAI (10)

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

create_request

Send a new data collection request to a recipient

get_campaign

Retrieve detailed information about a specific campaign

get_element_details

Retrieve details of a specific element (field/block) in a request

get_request

Retrieve details of a specific data request

get_team_info

Retrieve information about your team in Collect

get_user_info

Retrieve information about the currently authenticated user

list_campaigns

Retrieve a list of all data collection campaigns in Collect

list_messages

Retrieve a list of messages sent through Collect

list_requests

Retrieve all data requests for a specific campaign

send_message

Send a message to a recipient regarding a specific request

Example Prompts for Collect in CrewAI

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

"Show me all active data collection campaigns."

"Send a data request to 'John Doe' (john@example.com) for the 'KYC Process' campaign."

"Send an automatic reminder to all clients with missing documents in the 'Tax 2025' campaign."

Troubleshooting Collect MCP Server with CrewAI

Common issues when connecting Collect 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.

Collect + CrewAI FAQ

Common questions about integrating Collect 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.