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

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Hive AI through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "hive-ai": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Hive AI, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Hive AI
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
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 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.

LangChain's ecosystem of 500+ components combines seamlessly with Hive AI through native MCP adapters. Connect 10 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the Hive AI MCP Server with LangChain.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save the code and run python agent.py

04

Explore tools

The agent discovers 10 tools from Hive AI via MCP

Why Use LangChain with the Hive AI MCP Server

LangChain provides unique advantages when paired with Hive AI through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents — combine Hive AI MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across Hive AI queries for multi-turn workflows

Hive AI + LangChain Use Cases

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

01

RAG with live data: combine Hive AI tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query Hive AI, synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain Hive AI tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every Hive AI tool call, measure latency, and optimize your agent's performance

Hive AI MCP Tools for LangChain (10)

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

01

detect_ai_generated_image

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

02

detect_ai_generated_text

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

03

get_async_task_result

Retrieve the final moderation results for a completed task

04

get_async_task_status

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

05

get_project_details

Retrieve information and configuration for your Hive AI project

06

list_available_models

List all Hive AI models available for your project

07

moderate_audio_async

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

08

moderate_image

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

09

moderate_text

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

10

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 LangChain

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

01

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

02

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

03

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

Troubleshooting Hive AI MCP Server with LangChain

Common issues when connecting Hive AI to LangChain through the Vinkius, and how to resolve them.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Hive AI + LangChain FAQ

Common questions about integrating Hive AI MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

Connect Hive AI to LangChain

Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.