# How to connect Hugging Face to OpenClaw > Connect Hugging Face to OpenClaw in one click. 8 Hugging Face tools your agent can call from chat. No API keys. Web version: https://claw-link.dev/openclaw/hugging-face ClawLink gives OpenClaw a more practical Hugging Face setup than rolling your own integration. Install one ClawHub skill, connect Hugging Face in the browser, and OpenClaw can call real Hugging Face actions from any chat surface with no auth, token refresh, or tool wiring to build yourself. ## Hugging Face MCP for OpenClaw Looking for a Hugging Face MCP server for OpenClaw? ClawLink connects Hugging Face to OpenClaw and exposes 8 Hugging Face tools your agent can call over [MCP](https://claw-link.dev/learn/what-is-an-mcp-server), with [hosted auth](https://claw-link.dev/learn/oauth-for-ai-agents) and nothing to run or maintain yourself. Using Hermes instead? The [Hermes Hugging Face integration](https://claw-link.dev/hermes/hugging-face) works the same way. **Start here:** install the ClawLink plugin (`openclaw plugins install clawhub:clawlink-plugin`), pair it in the browser, then connect the app in the ClawLink dashboard. The interactive install prompt is on the web version of this page: https://claw-link.dev/openclaw/hugging-face ## Setup It takes three steps to connect OpenClaw to Hugging Face. 1. **Install ClawLink** — add the plugin to OpenClaw once. 2. **Connect Hugging Face** — one-click OAuth in the ClawLink dashboard. 3. **Use it from chat** — ask OpenClaw in plain English. **Alternative for any agent (no plugin needed):** if the OpenClaw plugin route isn't available or doesn't work, any AI agent with shell access can use the ClawLink CLI instead: ```bash npx -y @useclawlink/cli login # sign in via browser — no API key to paste npx -y @useclawlink/cli connect hugging-face # connect Hugging Face (browser OAuth) npx -y @useclawlink/cli actions hugging-face # list available actions npx -y @useclawlink/cli run hugging-face --input '' # execute (add --confirm for writes) ``` ## What the OpenClaw Hugging Face integration can do 8 Hugging Face tools are ready for OpenClaw once the account is connected. ### All 8 Hugging Face tools for OpenClaw | Tool | What it does | |---|---| | **Generate chat completion** `hugging_face_generate_chat_completion` | Generate a chat completion response | | **Generate embeddings** `hugging_face_generate_embeddings` | Convert text into vector embeddings | | **Get daily papers** `hugging_face_get_daily_papers` | Retrieve daily papers from Hugging Face | | **Filter dataset rows** `hugging_face_filter_dataset_rows` | Filter rows in a dataset split | | **Create collection** `hugging_face_create_collection` | Create a new collection on Hugging Face | | **Create ask access** `hugging_face_create_ask_access` | Request access to a gated repository | | **Check dataset validity** `hugging_face_check_dataset_validity` | Check whether a dataset is valid | | **Check models upload method** `hugging_face_check_models_upload_method` | Check upload method for model files | ## Example prompts **Generate Chat Completion** > Use Hugging Face to generate chat completion and walk me through the result in plain English. **Generate Embeddings** > Use Hugging Face to generate embeddings and walk me through the result in plain English. **Get Daily Papers** > Pull the relevant data from Hugging Face, summarize it in plain English, and point out anything that needs attention. **Filter Dataset Rows** > Use Hugging Face to filter dataset rows and walk me through the result in plain English. ## ClawLink vs. building it yourself The alternative to ClawLink is usually manual API key setup plus your own token handling, permission troubleshooting, and tool plumbing for OpenClaw. That is fine if you want to build and maintain the integration yourself. Most teams just want Hugging Face working from chat. | | Manual | ClawLink | |---|---|---| | **Credential handling** | Collect, validate, store, and rotate the Hugging Face API key yourself, then make sure every tool call uses the right account. | Users complete the hosted ClawLink setup once and the connected Hugging Face account becomes available to the agent without you building credential management. | | **Ongoing maintenance** | You own refresh logic, permission debugging, environment config, and every provider-specific edge case for Hugging Face. | ClawLink handles the repetitive integration plumbing so your team can focus on the workflow instead of the infrastructure. | | **Agent usability** | You still need to expose the right Hugging Face actions to the runtime in a format your agent can reliably use. | 8 tools for Hugging Face are already exposed through ClawLink, so the agent can read and act from chat immediately. | ## ClawLink vs. Composio Composio also exposes Hugging Face to AI agents. It is developer infrastructure: Python and TypeScript SDKs, an MCP server, and a catalog past 1,000 apps, aimed at teams shipping agent products. ClawLink is built for OpenClaw users instead. You install the plugin once, connect Hugging Face in the browser, and the 8 tools above work from chat. There is no SDK, no config file, and no API key handling. Choosing between them? Read the full [Composio alternatives](https://claw-link.dev/hub/composio-alternatives) comparison. ### OpenClaw installed the Hugging Face skill but can't call the tools The ClawHub skill teaches OpenClaw about Hugging Face, but the calls run through the ClawLink plugin and your connected account. Make sure Hugging Face is connected in the dashboard, then start a fresh chat so OpenClaw reloads the tool catalog. If OpenClaw runs as a persistent gateway, restart it so the new tools register. ### Connection succeeds but no tools appear Reconnect Hugging Face from the dashboard, then start a fresh chat if the runtime still has the old tool catalog loaded. ### The Hugging Face account is connected but the action fails Check whether the connected account has access to the workspace, inbox, store, or project you are trying to use. Most failures at this stage are permission mismatches, not ClawLink bugs. ### API key setup works but results look incomplete Double-check that the API key for Hugging Face has the right scopes or account access. A valid key can still be too limited for some reads or writes. ### Is there a OpenClaw Hugging Face integration? Yes. ClawLink is the fastest way to connect OpenClaw to Hugging Face: link your Hugging Face account once in the browser and OpenClaw can call the Hugging Face API through 8 ready-made tools — no custom code or token handling. ### How do I add Hugging Face to OpenClaw with ClawLink? Paste the setup prompt from this page into OpenClaw. It installs the ClawLink Hugging Face skill from ClawHub, then you click Connect in the dashboard to authorize Hugging Face. OpenClaw calls the tools from the next message — no config files or API keys. ### How long does it take to connect Hugging Face to OpenClaw? About two minutes. Sign in, click Connect next to Hugging Face in the dashboard, authenticate, and OpenClaw can use it from the next chat message. ### Why use ClawLink instead of wiring Hugging Face up myself? The alternative to ClawLink is usually manual API key setup plus your own token handling, permission troubleshooting, and tool plumbing for OpenClaw. That is fine if you want to build and maintain the integration yourself. Most teams just want Hugging Face working from chat. ### OpenClaw installed the Hugging Face skill but can't call the tools The ClawHub skill teaches OpenClaw about Hugging Face, but the calls run through the ClawLink plugin and your connected account. Make sure Hugging Face is connected in the dashboard, then start a fresh chat so OpenClaw reloads the tool catalog. If OpenClaw runs as a persistent gateway, restart it so the new tools register. ## Related - [OpenClaw ElevenLabs integration](https://claw-link.dev/openclaw/elevenlabs) — Generate speech and voice cloning - [HeyGen](https://claw-link.dev/openclaw/heygen) — Create AI-generated videos, avatars, and voice content - [Mem0 tools](https://claw-link.dev/openclaw/mem0) — Store and retrieve user memories and context for AI agents