Hive AI MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Hive AI through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Hive AI "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Hive AI?"
)
print(result.data)
asyncio.run(main())
* 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.
Pydantic AI validates every Hive AI tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.
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 Pydantic AI 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 Pydantic AI via MCP
Follow these steps to integrate the Hive AI MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Hive AI with type-safe schemas
Why Use Pydantic AI with the Hive AI MCP Server
Pydantic AI provides unique advantages when paired with Hive AI through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Hive AI integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Hive AI connection logic from agent behavior for testable, maintainable code
Hive AI + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Hive AI MCP Server delivers measurable value.
Type-safe data pipelines: query Hive AI with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Hive AI tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Hive AI and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Hive AI responses and write comprehensive agent tests
Hive AI MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Hive AI to Pydantic AI 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 Pydantic AI
Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI
Common issues when connecting Hive AI to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiHive AI + Pydantic AI FAQ
Common questions about integrating Hive AI MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect Hive AI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Hive AI to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.