Can I enrich a professional profile using a LinkedIn URL?

Yes! Use the `enrich_person` tool and provide the `li_profile_url`. Your agent will trigger the enrichment in Captain Data and return the detailed profile data.

How do I check my remaining API credits?

Simply ask the agent to `get_api_quotas`. It will retrieve your current usage and remaining quotas for different types of operations from your Captain Data account.

Does the integration allow finding companies by their domain name?

Yes. Use the `find_company` tool and provide the `domain` (e.g., 'google.com'). It will retrieve the basic company identifiers and metadata from the Captain Data database.

Captain Data MCP Server for CrewAI 11 tools — connect in under 2 minutes

Name: Captain Data
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 11 Tools Framework

Connect your CrewAI agents to Captain Data through Vinkius, pass the Edge URL in the `mcps` parameter and every Captain Data 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="Captain Data Specialist",
    goal="Help users interact with Captain Data effectively",
    backstory=(
        "You are an expert at leveraging Captain Data 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 Captain Data "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 11 available tools "
        "and what they can do."
    ),
)

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

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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 Captain Data MCP Server

Connect your Captain Data account to any AI agent and orchestrate your lead generation, market research, and data enrichment workflows through natural conversation.

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

People Discovery — Find specific professionals by name and company, or search by job titles and locations.
Profile Enrichment — Retrieve detailed LinkedIn profile data, including contact information and career history, using UIDs or URLs.
Company Research — Find companies by name or domain and retrieve deep firmographic data.
Automation Oversight — List and monitor automation jobs and workflows directly from your workspace.
Quota Management — Retrieve real-time API quotas and usage statistics to ensure your operations are on track.
Data Retrieval — Access extracted data from previous jobs using natural language.

The Captain Data MCP Server exposes 11 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 Captain Data to CrewAI via MCP

Follow these steps to integrate the Captain Data 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 11 tools from Captain Data

Why Use CrewAI with the Captain Data MCP Server

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

Captain Data + CrewAI Use Cases

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

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

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

Captain Data MCP Tools for CrewAI (11)

These 11 tools become available when you connect Captain Data to CrewAI via MCP:

enrich_company

Get deep firmographic data for a company

enrich_person

Get detailed profile data for a person using their UID or LinkedIn URL

find_company

Find a company by name or domain

find_people

Find a specific person by full name and optionally company name

get_account_info

Retrieve core account information

get_api_quotas

Retrieve current API quotas and usage

get_job_details

Get status and extracted data for a specific job

list_automation_jobs

List all automation jobs

list_workflows

List all configured workflows

search_companies

Search for companies by industry, size, or location

search_people

Search for people based on criteria like job title or location

Example Prompts for Captain Data in CrewAI

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

"Find people with the name 'Satya Nadella' at 'Microsoft'."

"Search for companies in the 'Software' industry located in 'California'."

"Enrich the company profile for the domain 'vinkius.com'."

Troubleshooting Captain Data MCP Server with CrewAI

Common issues when connecting Captain Data 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.

Captain Data + CrewAI FAQ

Common questions about integrating Captain Data 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.