Is an API Key required for Genderize.io?

No, you can use the service for free without an API key for up to 100 requests per day. For higher volume, you can obtain a key from genderize.io.

How accurate is the gender prediction?

The API returns a 'probability' score between 0.0 and 1.0. A score of 0.99 means the API is 99% certain of the associated gender based on its database.

Can I localise the results for a specific country?

Yes! Use the 'countryId' parameter with an ISO 3166-1 alpha-2 code (e.g., 'BR' for Brazil) to get results optimized for that specific region.

How many names can I check at once?

The 'estimate_genders_bulk' tool allows you to check up to 10 names in a single API request, which is efficient for processing small lists.

Genderize MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: Genderize
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Genderize through Vinkius, pass the Edge URL in the `mcps` parameter and every Genderize 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="Genderize Specialist",
    goal="Help users interact with Genderize effectively",
    backstory=(
        "You are an expert at leveraging Genderize 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 Genderize "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

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

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About Genderize MCP Server

Connect your AI agent to the Genderize.io database to automate gender estimation through the Model Context Protocol (MCP). Genderize.io is a specialized API that provides statistical probabilities for the gender associated with any first name, backed by a database of over 114 million records. This MCP server enables you to estimate genders for single or multiple names, localized by country, directly through natural conversation.

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

Key Features

Gender Estimation — Predict whether a first name is associated with a male or female identity based on global data.
Statistical Probability — Retrieve certainty scores (0.0 to 1.0) and the total data count used for each prediction.
Country Localization — Localize results by providing ISO country codes (e.g., 'US', 'BR', 'GB') to improve accuracy for regional naming patterns.
Batch Processing — Estimate genders for up to 10 names in a single request to process lead lists faster.
Regional Helpers — Quickly check names for specific countries like the USA, Brazil, UK, Spain, and France using dedicated tools.
No-Auth Free Tier — Start using the service immediately with up to 100 free requests per day without an API key.
Scale with API Keys — Optionally provide an API key to access higher rate limits for large-scale data enrichment.

The Genderize MCP Server exposes 8 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 Genderize to CrewAI via MCP

Follow these steps to integrate the Genderize 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 8 tools from Genderize

Why Use CrewAI with the Genderize MCP Server

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

Genderize + CrewAI Use Cases

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

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

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

Genderize MCP Tools for CrewAI (8)

These 8 tools become available when you connect Genderize to CrewAI via MCP:

estimate_gender

Predict gender by name

estimate_gender_brazil

Predict gender (Brazil)

estimate_gender_france

Predict gender (France)

estimate_gender_spain

Predict gender (Spain)

estimate_gender_uk

Predict gender (UK)

estimate_gender_us

Predict gender (USA)

estimate_genders_bulk

Predict multiple names

verify_api_connection

io API connectivity. Check connection

Example Prompts for Genderize in CrewAI

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

"Estimate the gender for the name 'Peter'."

"Predict the genders for these names: ['Alice', 'Bob', 'Charlie']."

"What is the predicted gender for 'Sasha' in Russia (RU)?"

Troubleshooting Genderize MCP Server with CrewAI

Common issues when connecting Genderize 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.

Genderize + CrewAI FAQ

Common questions about integrating Genderize 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.