Artificial Intelligence
Fal.ai MCP connector
The Fal.ai connector lets Claude, ChatGPT, Cursor, and any MCP client browse Fal.ai models, estimate and track model spend, review request history, and organize generated assets into collections, with every action logged under the person who made it.
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How it connects. Connects with an API key. The credential goes into a vault nobody reads back.
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One address. https://api.elaichi.ai/mcp, the same for every user.
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Their own access. An agent never gets more than the person it acts for.
How to connect
How to connect Fal.ai to Claude, ChatGPT or Cursor
Two steps, about a minute.
In Elaichi
Connect Fal.ai once
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Open Connections, choose Add connection, and pick Fal.ai.
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Optionally set Share with to give a team access, then press Connect.
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Paste a Fal.ai API key. One person generates a token in Fal.ai and pastes it once. Everyone else works through Share with, and never sees it.
The credential is vaulted. Nobody reads it back, not even the AI.
Add connection
Choose a connector.
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.
Connect Fal.ai to Claude
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1
Open Customize, then Connectors.
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2
Press Add.
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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.
Connect Fal.ai to ChatGPT
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1
Open Plugins, then press the + button.
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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.
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4
Press Create, then sign in and approve.
Works on the web today. The plugin directory lives at chatgpt.com/plugins.
Connect Fal.ai to Cursor
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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 Fal.ai to any MCP client
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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.
Use cases
What teams do with Fal.ai through Elaichi
Every one of these runs inside the access the person already has, and lands in the same audit log.
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Engineering
Pick the right model before you build
Ask which Fal.ai models are available for a task, compare their pricing side by side, and get a cost estimate for the volume you expect before anyone writes a line of code.
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Finance
Reconcile the month's Fal.ai bill
Pull billing events and usage by model for the period, match them against the invoice, and spot which endpoints drove the spike.
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Creative
Keep generated assets in order
Find assets by tag, group them into collections for a campaign or client, favorite the keepers, and move the rest where they belong.
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Product
See which endpoints are actually used
Review request analytics and per-endpoint traffic to learn which models your features lean on and which ones nobody calls anymore.
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Operations
Trace a failed or slow request
Search Fal.ai request history for a specific job, check what was sent and when, and clean out old request payloads in bulk when they are no longer needed.
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Engineering
Document and reuse existing workflows
List the workflows already set up in Fal.ai, open one to see how it is wired, and create a new one from a plain description of the steps.
Try asking
- “Which Fal.ai models cost us the most this month?”
- “Show failed Fal.ai requests by endpoint this week.”
- “List Fal.ai workflows created since Monday and their owners.”
AI tools
Fal.ai tools for your AI agents
74 tools are ready to call through Elaichi's MCP endpoint the moment you connect Fal.ai, governed by the same roles, restrictions, and audit log as everything else in Elaichi.
No tools match your search.
See it in Elaichi
What connecting Fal.ai gets you
6 screens from the product, each doing one job for your Fal.ai account.
The agent
Ask about Fal.ai runs, get answers.
Plain language questions answered from live Fal.ai models, workflows and requests.
- models
- workflows
- requests
- assets
Ask Elaichi to work across your apps.
Which Fal.ai models cost us the most this month?
Show failed Fal.ai requests by endpoint this week.
List Fal.ai workflows created since Monday and their owners.
Also runs in Claude, ChatGPT or Cursor
MCP clients
Claude, ChatGPT and Cursor reach Fal.ai.
One org MCP endpoint over OAuth, no SDK and no shared API key.
Copy the endpoint
Tool catalog
74 Fal.ai tools ready to call.
Models, pricing, workflows, assets and requests covered without custom code.
- List all Fal.ai models
- List all Fal.ai models pricings
- Create a Fal.ai pricing estimate
- List all Fal.ai models usages
Toolboxes
Every team gets its own Fal.ai toolbox.
Toolboxes scoped per team, so each group sees the Fal.ai tools it needs.
- ML Engineering
- Platform
- Finance
- Product
Shared connections
Share a Fal.ai account, never the key.
See who connected each account and how many teams and members use it.
- ML Engineering
- Platform
- Finance
- Product Analytics
Audit log
Answer who called Fal.ai and when.
Append-only log of time, person, action, type and Fal.ai resource touched.
- When
- Who
- What happened
- Type
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 drafts your Fal.ai digest.
Six steps fetch requests, group them, draft, wait for approval, then post back.
Fal.ai digest
Run 418 · started 2 minutes ago · on behalf of Emma Laurent
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✓
Schedule
Every weekday at 08:00
0.2s -
✓
Fetch models
Fal.ai
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
Fal.ai
Queued
Collections and dashboards
Fal.ai usage counted, not asked for.
Four metrics, 14 days of workflow runs and a team breakdown, refreshed on schedule.
Fal.ai health
Refreshed 4 minutes ago · every 15 minutes · from the models collection
Models
1,284 ↓ 12%
Workflows
96 ↓ 8%
Needs attention
3 ↑ 2
Updated this week
412 ↑ 9%
Models created
Last 14 days
By team
Share of activity
ML Engineering 34%
Platform 27%
Finance 21%
Product Analytics 18%
FAQ
Frequently asked questions
How do I connect Fal.ai to Claude?
Connect Fal.ai in Elaichi first: you paste a Fal.ai API key into Elaichi, and that is the whole sign-in step, with no OAuth application to register and no client ID or secret to generate. Then in Claude go to Customize, then Connectors, then Add, and paste the endpoint https://api.elaichi.ai/mcp. Sign in to Elaichi when Claude asks, and Fal.ai is available in your conversations.
Does Fal.ai work with ChatGPT and Cursor as well as Claude?
Yes. Once Fal.ai 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 Fal.ai once and every client picks it up.
What can an AI agent actually do with my Fal.ai data?
An agent can list the Fal.ai models you have access to, compare their prices, estimate what a batch of requests will cost, and report usage, analytics, and billing events by model or endpoint. It can search past requests, list and create workflows, and organize generated assets into collections, including favoriting, moving, or deleting a collection. Because Fal.ai exposes many actions, short concrete asks like "show usage by model for March" work better than long paragraphs.
Does connecting Fal.ai give the AI access to my whole Fal.ai account?
The agent works inside the access of the Fal.ai API key that was connected, so it can only see the models, requests, assets, and billing the key itself can see. Elaichi can narrow that further with per-action restrictions, for example allowing usage reports but not deletions. Elaichi never widens access beyond what Fal.ai already grants.
Can I stop an agent from deleting or changing things in Fal.ai?
Yes. Restrictions in Elaichi apply per action, so you can allow reading Fal.ai models, usage, and assets while blocking collection deletion or bulk removal of request payloads. A blocked action is never advertised to Claude, ChatGPT, or Cursor at all, so no prompt, however worded, can reach it.
What happens to a Fal.ai connection when someone leaves?
Offboarding a person in Elaichi ends their access to Fal.ai and every other connector at once, without touching the Fal.ai key. A shared Fal.ai connection keeps working for everyone else on the team. If you ever want Fal.ai gone entirely, disconnecting it once in Elaichi removes it from Claude, ChatGPT, Cursor, and every other client at the same time.
Put Fal.ai in front of your team
Fourteen days on Gold, no credit card. Connect it once and pick what each team can call.