Use Hugging Face with your AI.
Connect your account once and let the AI you already use work with it, without building another integration. Transform the world's largest ML hub into your growth engine. Deploy autonomous agents to intercept trending discussions and engage the AI elite in real-time.
Developed, maintained, and hosted by Vinkius.
MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED
Waiting for input…
Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.
Complete set · 8 capabilities
The complete Hugging Face capability set.
These are the exact actions your AI can choose when you ask it to work with Hugging Face.
01-04
4 capabilities in this set.
Part of 8 available through Hugging Face.
- 01
Get discussion details
You MUST read the discussion details before engaging or commenting to fully understand the context. Get the full details and comments of a specific Hugging Face discussion
- 02
Get repo discussions
Use this to monitor community activity and identify pain points. Get discussions/issues for a specific Hugging Face repository
- 03
Search repositories
Useful for identifying high-value community engagement opportunities based on keywords. Search for Hugging Face repositories (models, datasets, spaces)
- 04
Comment discussion
Use Markdown formatting. Add a comment to an existing Hugging Face discussion
05-08
4 capabilities in this set.
Part of 8 available through Hugging Face.
- 05
Get repo intelligence
Use this for rapid market awareness before deciding to engage. Get a comprehensive intelligence report for a Hugging Face repository
- 06
Get trending repositories
Essential for understanding community interests and providing timely, relevant engagement. Get the top trending repositories on Hugging Face
- 07
Scan target discussions
Use this to find relevant discussions based on targeted keywords across the most active projects. Scan trending Hugging Face repositories for discussions matching a specific keyword
- 08
Create discussion
Ensure the title is clear and the description provides all necessary context. Create a new discussion or issue in a Hugging Face repository
Observed, not estimated
748ms average. Fast in production.
Hugging Face is checked daily against the live service.
- Fastest day
- 548ms
- Slowest day
- 887ms
- 14-day trend
- Slowing+53%
Connect your client
One URL. Every client.
Activate the Connector, copy your link, and paste it into the client you already use. 8 capabilities arrive ready to run.
Preview access · not provider authentication
The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Hugging Face, so you can see the experience inside your AI.
It does not authenticate your account with Hugging Face. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.
Hugging Face Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_5HaPf646XIGEkHF6B1qWXsBOdC8KasfqJUTQe6ae/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Hugging Face capabilities are ready to use.
{
"mcpServers": {
"hugging-face-discussions-mcp": {
"url": "https://edge.vinkius.com/vk_preview_5HaPf646XIGEkHF6B1qWXsBOdC8KasfqJUTQe6ae/mcp"
}
}
}
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Step-by-step instructions for each client are in the guide. How to connect
FAQ
Questions Hugging Face owners ask.
- 01
How do I find my Hugging Face Access Token?
Go to your Hugging Face account settings, under Access Tokens, and create a new fine-grained token. Ensure it has permissions to read and interact with discussions on the specific repositories you want to target.
- 02
Can the agent post replies automatically?
Yes. Using the comment_discussion capability, your agent can write and post Markdown replies directly into community threads.
- 03
How does the target scanning work?
The scan_target_discussions capability fetches the top trending repositories (models, datasets, etc.) and then iterates through their active discussions, filtering for the exact keyword you specify. It's highly efficient for finding interception points.
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