How do I find my Hive AI API Keys?

Log in to your Hive AI dashboard, select a project (e.g., a Visual or Text project), and navigate to the **Settings** or **API** section. Note that each project type requires its own unique API key.

What is the difference between Synchronous and Asynchronous moderation?

Synchronous moderation (`moderate_text`, `moderate_image`) returns results instantly and is best for real-time interactions. Asynchronous moderation (`moderate_video_async`) is used for larger files and requires polling the task status or using a callback.

Can this integration detect deepfakes or AI-generated voices?

Yes! Hive AI provides specialized models for detecting AI-generated content across text, images, video, and audio. Use the `detect_ai_generated_text` and `detect_ai_generated_image` tools for these checks.

Is the integration secure for sensitive content?

Absolutely. The integration uses official Hive AI Token authentication over HTTPS. Your credentials and analyzed content are encrypted and stored securely within the Vinkius Cloud infrastructure.

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

Name: Hive AI
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Connect your Hive AI moderation account to any AI agent and take full control of your content safety and compliance workflows through natural conversation.

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

Real-time Moderation — Perform synchronous moderation for text and images to filter hate speech, violence, and NSFW content instantly.
AI Content Detection — Identify if text, images, or audio were created using generative AI models like GPT-4, Midjourney, or DALL-E.
Asynchronous Processing — Submits large video and audio files for deep moderation and speech-to-text analysis.
Task Monitoring — Track the status and retrieve results for background moderation tasks using unique task IDs.
Model Insights — List available Hive AI models and retrieve project-specific configurations for both visual and text projects.
Compliance Oversight — Access detailed moderation scores and classes to ensure your platform remains safe and professional.

The Hive AI 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 Hive AI to CrewAI via MCP

Follow these steps to integrate the Hive AI 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 Hive AI

Why Use CrewAI with the Hive AI MCP Server

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

Hive AI + CrewAI Use Cases

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

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

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

Hive AI MCP Tools for CrewAI (10)

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

detect_ai_generated_image

Identify if an image was created using generative AI (e.g., Midjourney, DALL-E)

detect_ai_generated_text

Detect if a block of text was generated by an AI model (e.g., GPT-4)

get_async_task_result

Retrieve the final moderation results for a completed task

get_async_task_status

Use the task ID returned when the task was created. Check the status of an asynchronous moderation task

get_project_details

Retrieve information and configuration for your Hive AI project

list_available_models

List all Hive AI models available for your project

moderate_audio_async

Returns a task ID. Start an asynchronous moderation task for an audio file

moderate_image

Provide a publicly accessible URL. Perform real-time image moderation using a URL

moderate_text

Use this to verify user-generated content before publication. Perform real-time text moderation for safety and compliance

moderate_video_async

Returns a task ID for later status checking. Start an asynchronous moderation task for a video file

Example Prompts for Hive AI in CrewAI

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

"Moderate this text for safety: 'I will destroy everything you love.'"

"Check if this image was created by AI: 'https://example.com/art.jpg'."

"Start a moderation task for this video: 'https://example.com/upload.mp4'."

Troubleshooting Hive AI MCP Server with CrewAI

Common issues when connecting Hive AI 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.

Hive AI + CrewAI FAQ

Common questions about integrating Hive AI 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.