Can my team share one Hugging Face connection?

Yes. One person connects Hugging Face in Elaichi and shares the connection with a team, and nobody else ever handles a token. Each teammate still signs in to Elaichi as themselves, so the audit log names the person who searched the Hub or read a repository, not a shared account.

Artificial Intelligence

Hugging Face MCP connector

The Hugging Face connector brings model, dataset and Space repositories into Elaichi, so Claude, ChatGPT, Cursor and the Elaichi Agent can search the Hub, read model cards and browse repository files as the signed-in person.

Connect on Elaichi How to connect

How it connects. Connects over OAuth. The credential goes into a vault nobody reads back.
One address. https://api.elaichi.ai/mcp, the same for every user.
Their own access. An agent never gets more than the person it acts for.

4 tools

How to connect

How to connect Hugging Face to Claude, ChatGPT or Cursor

Two steps, about a minute.

In Elaichi

Connect Hugging Face once

Open Connections, choose Add connection, and pick Hugging Face.
Optionally set Share with to give a team access, then press Connect.
Approve it in Hugging Face. Hugging Face's own window opens. Whoever approves it decides what this connection can reach.

The credential is vaulted. Nobody reads it back, not even the AI.

Add connection

Choose a connector.

hugging face

All categories

Hugging Face

AirOps

Algolia

Botpress

Chatvolt

Cohere

In your AI client

Point it at one endpoint

Everyone in the organization uses the same address, and each person only ever reaches what their own account allows.

Hugging Face MCP connector for Claude

1

Open Customize, then Connectors.
2

Press Add.
3

Name it, paste the MCP server URL, then Continue.

https://api.elaichi.ai/mcp
4

Sign in and approve.

On Team and Enterprise, an Owner adds it once. Everyone else turns it on for themselves.

Hugging Face MCP connector for ChatGPT

1

Open Plugins, then press the + button.
2

Name it and paste the endpoint into Server URL.

https://api.elaichi.ai/mcp
3

Leave Authentication on OAuth, then tick the risk acknowledgement.
4

Press Create, then sign in and approve.

Works on the web today. The plugin directory lives at chatgpt.com/plugins.

Hugging Face MCP connector for Cursor

1

Open ~/.cursor/mcp.json.
2

Add the endpoint under mcpServers.

https://api.elaichi.ai/mcp
3

Reload Cursor, then sign in and approve.

~/.cursor/mcp.json

{
  "mcpServers": {
    "elaichi": {
      "url": "https://api.elaichi.ai/mcp"
    }
  }
}

Set up per machine, so repeat it on each computer you work from.

Connect Hugging Face to any MCP client

1

Add the endpoint as a remote MCP server.

https://api.elaichi.ai/mcp
2

Sign in and approve.

{
  "mcpServers": {
    "elaichi": {
      "url": "https://api.elaichi.ai/mcp"
    }
  }
}

The Elaichi Agent already has these tools, with nothing to set up.

Connect Hugging Face on Elaichi See pricing

Use cases

What teams do with Hugging Face through Elaichi

Every one of these runs inside the access the person already has, and lands in the same audit log.

ML engineering

Shortlist candidate models before a build

Ask for the most downloaded text classification models on Hugging Face under an Apache license, then compare their model cards without opening a dozen tabs.
Data science

Find a dataset that fits the task

Search the Hub for datasets by task, language and size, then read the dataset card and look through the files before you commit to anything.
Research

Read a model card without leaving the chat

Pull the details of a specific repository, including its tags, license, downloads and recent updates, and have the agent summarize what matters for your paper or experiment.
Compliance

Check a model's license before anyone ships it

Have the agent confirm the license on each Hugging Face repository your teams are using and flag any that need a closer look.
Product

Explain what a model does in plain language

Ask for a non-technical summary of a model's card so a product review can move forward without waiting on an engineer.
Developer relations

Keep track of your organization's public repositories

List the models, datasets and Spaces published under your organization and read their cards to see which ones are out of date.

Try asking

“Find Apache licensed text classification models with the most downloads”
“Which French sentiment datasets have more than 10k downloads”
“List the files in our organization's latest model repository”

See all 4 Hugging Face tools below

Compare

Elaichi vs Zapier MCP vs Composio for Hugging Face

All three can connect Hugging Face to an AI assistant, and all three have admin controls. They differ in where access lives and how you pay.

Elaichi compared with Zapier MCP and Composio for Hugging Face, by what to check
What to check	Elaichi	Zapier MCP	Composio
Where the AI connects	One address for the whole organization. `https://api.elaichi.ai/mcp`	A server per member, created at sign-in.	An MCP endpoint per team, or an SDK.
Control over Hugging Face tools	Allow or restrict single Hugging Face tools, per role or user.	App and action restrictions on the account.	Role permissions, down to the action.
Record of calls	One audit entry per Hugging Face call.	A History tab of tool calls.	A log of every tool call.
Single sign-on	SAML or OIDC, plus SCIM, on Gold.	SAML on Enterprise.	SAML and OIDC on Enterprise.
Price	$15 per user per month.	2 tasks per successful call.	Billed per tool call.

Sources: Zapier MCP docs, security, usage; Composio docs, gateway, enterprise, pricing. Checked September 2026.

Longer take: Zapier MCP alternative and when you don't need an MCP gateway.

AI tools

Hugging Face tools for your AI agents

4 tools are ready to call through Elaichi's MCP endpoint the moment you connect Hugging Face, governed by the same roles, restrictions, and audit log as everything else in Elaichi. Hugging Face builds and runs these tools.

See it in Elaichi

What connecting Hugging Face gets you

6 screens from the product, each doing one job for your Hugging Face account.

The agent

Ask about models and get live answers.

Search models, datasets and Spaces on Hugging Face in plain language, as yourself.

models
datasets
spaces
files

Ask Elaichi to work across your apps.

Find Apache licensed text classification models with the most downloads

Which French sentiment datasets have more than 10k downloads

List the files in our organization's latest model repository

Also runs in Claude, ChatGPT or Cursor

MCP clients

One endpoint puts Hugging Face in every client.

Claude, ChatGPT and Cursor connect once over OAuth, with no SDK and no shared token.

ElaichiMCP clients

Claude

ChatGPT

Cursor

Copy the endpoint

https://api.elaichi.ai/mcp

Client	Connected by	Status	Last used
Claude	E Emily Carter	• Connected	4 minutes ago
Cursor	M Megan Brooks	• Connected	2 hours ago
ChatGPT	R Ryan Hayes	• Connected	Yesterday

Tool catalog

4 Hugging Face tools, ready with no code.

Search the Hub, read repository details, browse files and check the signed-in account.

Hf whoami
Hub repo search
Hub repo details
Hf fs

ElaichiTools

Tool	Action	Description
Hf whoami	Action	Inspect the current Hugging Face authentication context, including the account, visible organization memberships, and credential access details. Read-only and never returns credential values.
Hub repo search	Search	Search Hugging Face repositories with a shared query interface. You can target models, datasets, spaces, or aggregate across multiple repo types in one call. Include links to repositories in your response.
Hub repo details	Action	Get details for one or more Hugging Face repos (model, dataset, or space). Auto-detects type unless specified. For datasets, use operations: overview, dataset_structure, dataset_preview. Use dataset_structure first to discover configs, splits, sizes, and schema. Use…
Hf fs	Action	When to use: Hugging Face Hub models, datasets, Spaces, collections, papers, daily papers, today's trending models, current paper leaderboard, docs, and repository files. Examples: {"operations":[{"cmd":"ls","args":["hf://models/trending","--limit","10"]}]}…

Toolboxes

Every team gets its own Hugging Face toolbox.

Research, data science and compliance each see the tools their work needs.

Research
Data science
ML engineering
Compliance

ElaichiToolboxes

Name	Source template	Tools	Created
Research toolbox Hugging Face · model discovery and cards	Hugging Face starter	18	Mar 4, 2026
Data science toolbox Hugging Face · datasets and files	—	9	Mar 2, 2026
ML engineering toolbox Hugging Face · model repositories and weights	—	24	Feb 27, 2026
Compliance toolbox Hugging Face · licenses and provenance	Hugging Face starter	6	Feb 19, 2026
Product toolbox Hugging Face · model summaries for reviews	—	31	Jan 30, 2026
Developer relations toolbox Hugging Face · the organization's public repositories	—	12	Jan 22, 2026

Shared connections

Teammates work through one connection, never a token.

One person connects Hugging Face, shares with teams, and nobody else handles a credential.

Research
Data science
ML platform
Compliance

ElaichiConnections

Connection	Scope	Status	Access
HU Hugging Face (Research) Connected by Emily Carter	Personal	• Active	1 team · 6 members
HU Hugging Face (Data science) Connected by Jake Morgan	Organization	• Active	3 teams · 24 members
HU Hugging Face (ML platform) Connected by Megan Brooks	Organization	• Active	2 teams · 11 members
HU Hugging Face (Compliance) Connected by Tyler Reed	Personal	• Needs re-auth	1 team · 3 members
HU Hugging Face (Product) Connected by Ryan Hayes	Personal	• Active	Not shared
HU Hugging Face (DevRel) Connected by Ashley Parker	Personal	• Active	2 teams · 9 members

Audit log

Every Hugging Face call is on the record.

When, who, what happened and which repository, written to an append-only log.

When
Who
What happened
Type

ElaichiAudit log

When	Who	What happened	Type
2 minutes ago Mar 6, 2026, 3:10 PM	E Emily Carter [email protected]	Restriction Created	Access
8 minutes ago Mar 6, 2026, 3:04 PM	J Jake Morgan [email protected]	Restriction Updated	Access
14 minutes ago Mar 6, 2026, 2:58 PM	M Megan Brooks [email protected]	Role Assigned	Access
20 minutes ago Mar 6, 2026, 2:52 PM	T Tyler Reed [email protected]	Hugging Face Users Updated	MCP
26 minutes ago Mar 6, 2026, 2:46 PM	R Ryan Hayes [email protected]	Hugging Face Models Created	MCP
32 minutes ago Mar 6, 2026, 2:40 PM	A Ashley Parker [email protected]	Hugging Face Models List	Toolbox

Launching soon

From answering questions to doing the work

A person no longer has to ask. A trigger starts the work, inside the same permissions and the same audit log as everything else. Automations and live dashboards are launching soon, on the Black plan.

Automations

A schedule starts the work, a person approves.

New Hugging Face repositories are fetched, grouped, drafted into a digest, approved and posted back.

Hugging Face digest

Run 418 · started 2 minutes ago · on behalf of Emily Carter

Run now

✓

Schedule

Every weekday at 8:00 AM

0.2s
✓

Fetch models

Hugging Face

1.4s
✓

Group by owner

Transform

0.1s
✓

Draft the digest

Agent step

Ran with 4 tools, returned a structured summary

6.2s
Approve the digest

Needs approval

Assigned to Michael Brennan

Approve Deny
Post the digest

Hugging Face

Queued

Collections and dashboards

Hugging Face health, computed without a model.

Four metrics, 14 days of repositories created and a team breakdown, refreshed on schedule.

Hugging Face health

Refreshed 4 minutes ago · every 15 minutes · from the models collection

Live

Models

1,284 ↓ 12%

Datasets

96 ↓ 8%

Needs attention

3 ↑ 2

Updated this week

412 ↑ 9%

Models created

Last 14 days

By team

Share of activity

Research 34%

Data science 27%

ML platform 21%

Compliance 18%

Related connectors

More from the catalog

Browse all 500+ connectors →

FAQ

Frequently asked questions

How do I connect Hugging Face to Claude?

Connect Hugging Face in Elaichi first: pick it from the catalog and sign in with your Hugging Face account over OAuth, approving the access it asks for. There is no OAuth application to register and no client ID or secret to generate. Then in Claude open Customize, then Connectors, then Add, and paste https://api.elaichi.ai/mcp. Claude signs you in through Elaichi and Hugging Face is available in your next conversation.

Does Hugging Face work with ChatGPT and Cursor as well as Claude?

Yes. Once Hugging Face is connected in Elaichi, the same endpoint, https://api.elaichi.ai/mcp, works in Claude, ChatGPT, Cursor, any other MCP client and the Elaichi Agent. You connect Hugging Face once and every client you use picks it up.

What can an AI agent actually do with my Hugging Face data?

With Hugging Face connected, an agent can search the Hub for models, datasets and Spaces, read a repository's card, license, tags and download counts, browse the files inside a repository, and confirm which Hugging Face account it is working as. Short, concrete asks work best, such as the license of a named model or the most downloaded datasets for a task, rather than long multi-part sentences.

Does connecting Hugging Face give the AI access to all my repositories and organizations?

No. Every call to Hugging Face runs as the person who signed in, so the agent sees only the public repositories and the private repositories and organizations that person can already open on Hugging Face. Elaichi can narrow that further with roles and restrictions, but it can never widen what Hugging Face itself allows.

Can I stop an agent from changing things in Hugging Face?

Yes. Restrictions in Elaichi apply per action on the Hugging Face connector, so you can leave searching and reading open while closing off anything you do not want an agent to touch. A restricted action is never advertised to Claude, ChatGPT or Cursor at all, so no prompt can reach it.

What happens to a Hugging Face connection when someone leaves?

Offboarding a person in Elaichi ends their access to Hugging Face through every client at once. A Hugging Face connection shared with a team keeps working for everyone else, and if you disconnect Hugging Face in Elaichi it disappears from Claude, ChatGPT, Cursor and the Elaichi Agent in one step.

Does the Hugging Face MCP connector work with Gemini, Codex, Claude Code or other MCP clients?

Yes. Hugging Face is reached over the same MCP endpoint every client uses, so anything that speaks MCP can call it — Gemini, Codex, Claude Code, Windsurf, Cline, Zed and OpenCode among them — alongside Claude, ChatGPT, Cursor, and the Elaichi Agent. The tools on offer and the access behind them are identical whichever client asks. Only the setup screen differs.

Is Elaichi an alternative to Zapier MCP for Hugging Face?

Yes. Both let Claude, ChatGPT or Cursor use Hugging Face. Zapier MCP fits a team that already automates in Zapier, since each person signs in and acts as themselves in that account. Elaichi fits when IT wants one address for the whole company, per-tool rules by role, and a record of every Hugging Face call.

How is Elaichi different from Composio for Hugging Face?

Composio gives AI agents tools and sign-in handling across 1,000+ apps, for developers building agents or people using an assistant, billed per tool call. Elaichi gives a company's own people governed access to Hugging Face: one address, restrictions per role or user, and $15 per user per month. Both have role permissions and a log of every call.

Put Hugging Face in front of your team

14 days on Gold, no credit card. Connect it once and pick what each team can call.

Connect Hugging Face Talk to us

Works with: and any other MCP client, or the Elaichi Agent.
When the trial ends: Nothing is deleted. Connections, roles and the audit log stay where they are, so subscribing picks up exactly where you left off.