Hive AI MCP. Automate Content Safety for Text and Media
Hive AI connects content safety and compliance directly into your workflow. It moderates text, images, video, and audio in real-time or runs deep background checks. Use this MCP to instantly filter out hate speech, NSFW material, spam, or detect if uploaded media was created by generative AI.
Give Claude and any AI agent real-world access
The system filters out hate speech, violence, and NSFW content from text or images instantly.
It scans uploaded text and images to determine the probability that they were created using generative AI models.
You track large moderation jobs for video or audio files by checking a unique task status ID.
It lists all available models and retrieves project-specific settings to make sure your checks run correctly.
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What AI agents can do with Hive AI with 10 Tools
These tools allow you to perform every type of media check imaginable, from simple text moderation to complex background analysis on large videos.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Hive AI MCPGet Project Details
Retrieves configuration information specific to your Hive AI project setup.
Detect Ai Generated Image
Determines if a provided image was generated by tools like Midjourney or DALL-E.
Detect Ai Generated Text
Checks a block of text to see the probability it originated from an AI model.
Get Async Task Result
Pulls the final moderation results for a background task that has finished...
Get Async Task Status
Checks the current status of an asynchronous moderation job using its unique ID.
List Available Models
Provides a list of all specific content analysis models available for your project use.
Moderate Audio Async
Starts a background moderation process for an audio file and returns a task ID.
Moderate Image
Performs real-time safety checks on an image using a publicly accessible URL.
Moderate Text
Runs immediate moderation on text input to check for compliance and safety rules.
Moderate Video Async
Starts a background moderation task for video content, giving you an ID for later...
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Hive AI, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Hive AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS CLOUD
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
The Manual Content Review Grind
Think about what happens today: A community manager gets a notification for questionable content. They click the link, open the image in one tab, copy the text from another section, and then switch to a third dashboard just to check the user's history. This process requires constant context switching, multiple logins, and hours of tedious, repetitive review.
With this MCP, your agent handles that entire chain of custody automatically. Instead of manual clicks and tabs, you simply ask your agent: 'Is this safe?' It runs checks across text, images, or video in one go, delivering a clear report on compliance status.
Hive AI Moderation Tools
You eliminate the need to write custom code for every single policy check. You don't have to build separate pipelines just because you started handling audio files instead of images, or if you decide to add text moderation later. Everything is wrapped in a unified conversation.
The difference now is that your platform's safety layer isn't an afterthought; it's part of the core data flow. You get immediate compliance oversight without hiring more human reviewers.
What Hive AI MCP does for your AI
Content safety used to mean manual review—a nightmare of endless tabs and flagged posts. Now, your agent handles it all. This MCP lets you run comprehensive checks on anything a user uploads, from simple text comments to massive video files. You can filter out bad language instantly using real-time moderation or submit large videos for deep analysis that runs in the background.
Need to know if an image is fake? The system detects AI fingerprints across images and audio. Whether your platform needs constant compliance oversight or just wants to block obvious spam, this MCP gives you control. Connecting through Vinkius means your agent can access all these safety tools without needing a dozen separate API keys.
019d75b1-da3e-717b-b64b-d2352032393f How to set up Hive AI MCP
The bottom line is that your AI client treats this MCP like a specialized Content Safety Lead, allowing you to enforce platform guidelines using natural conversation.
You subscribe to this MCP and enter your Hive AI Visual and Text project API Keys.
Your agent sends the content (text, image URL, or file) it needs checked against safety policies.
The system returns a moderation score and classification, telling you if the content is safe, flagged, or violates specific rules.
Who uses Hive AI MCP
This connects with Community Managers who are drowning in manual content review. It's for Platform Developers building user-facing features that must be safe by design, and Trust & Safety specialists who need automated compliance tracking across diverse media types.
They monitor real-time chats and image uploads to maintain community standards without manually checking every post.
They integrate deep content analysis into the data flow, ensuring that user inputs meet safety requirements before being saved or published.
They automate rule enforcement by instantly retrieving moderation scores for flagged content and running background checks on large media uploads.
Benefits of connecting Hive AI MCP
You don't have to manually check every post. By using moderate_text, your agent automatically filters out hate speech or violent language before it hits the public feed.
Dealing with deepfakes is a pain point solved by AI detection. The detect_ai_generated_image tool instantly flags if an uploaded picture was machine-made.
Processing large files used to mean hours of waiting and manual follow-up. Now, starting background jobs via moderate_video_async lets you check massive video libraries without blocking your workflow.
Platform compliance is easier when the tools do the heavy lifting. You can use list_available_models to ensure your agent is always running against the most current safety standards.
The system gives you full visibility into content risk. By using get_async_task_status, you know exactly when a big background job finishes, so you can act on the results immediately.
Hive AI MCP use cases
Reviewing user-uploaded artwork
A Community Manager gets an image upload and needs to verify it's legitimate. They ask their agent to check for AI artifacts using detect_ai_generated_image. The agent instantly reports a 99% likelihood the art was machine-generated, allowing the moderator to reject it based on policy.
Moderating API inputs
A developer is building a public-facing form and needs to make sure submissions are clean. They call moderate_text on every input field. If the text score for 'Hate Speech' exceeds 80%, the agent blocks submission immediately.
Handling long video content
A platform needs to vet a user-submitted training video that's three hours long. Instead of reviewing it manually, they call moderate_video_async. They get a task ID and then periodically use get_async_task_status until the final safety report is ready.
Screening chat messages for spam
A live chat system receives thousands of rapid-fire messages. Before displaying any message, it runs a quick check using moderate_text. This prevents immediate publication of explicit or rule-violating language in real time.
Hive AI MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Checking everything synchronously
Trying to run deep moderation on a 50GB video file using simple, real-time tools. The agent times out or simply fails because the process is too heavy for instant feedback.
For large files like videos and audio, use asynchronous methods. First, call moderate_video_async to get a task ID, then repeatedly check that status using get_async_task_status until you retrieve the final results with get_async_task_result.
Assuming content is clean
Publishing user-generated text without checking it, assuming a simple filter will catch obvious profanity. This fails when users use complex coded language or subtle hate speech.
Always run moderate_text on all user inputs. The detailed moderation scores give you compliance oversight beyond just binary block/allow decisions.
Using outdated models
Running a safety check and getting inaccurate results because the underlying model hasn't been updated to detect new types of deepfakes or spam.
Start by calling list_available_models to confirm your agent is using the most current, approved analysis models for maximum detection accuracy.
When to use Hive AI MCP
Use this MCP if your content safety needs are complex: you handle multiple media types (text, images, video), need deep AI fingerprinting, or process high volumes of uploads. It's ideal when you require both real-time blocking and long-term background analysis.
Don't use it if all you need is simple, basic text filtering that runs in a single API call without needing asynchronous follow-up. If your needs are limited to just one type of content (e.g., only checking user names for profanity), a simpler, dedicated tool might suffice. But if the goal is comprehensive platform compliance across an entire media stack, this MCP handles it all.
Frequently asked questions about Hive AI MCP
How do I check if a video violates policy using Hive AI? +
You start by calling moderate_video_async with the video's URL. This returns a unique task ID. You must then use get_async_task_status and later get_async_task_result to get the final report once processing is complete.
Can Hive AI detect if I used Midjourney? +
Yes, you can run an image check using detect_ai_generated_image. This tool provides a probability score indicating whether the media was created by generative AI models.
Is moderate_text for real-time use? +
Yes, moderate_text is designed for instant checks. You run it on user input to verify compliance and safety rules immediately before publishing the content.
What if I need to know what other models are available? +
Use the list_available_models tool first. This shows you all the specific Hive AI models that can be applied to your project for various types of analysis.
Does this MCP handle audio files? +
It does, but because audio is complex, it requires an asynchronous process. You initiate the moderation using moderate_audio_async and track the outcome with the corresponding status tools.