Monte Carlo MCP connector
The Monte Carlo connector brings data alerts, incidents, assets, lineage and monitors into Claude, ChatGPT, Cursor and the Elaichi agent, so your team can investigate data issues from any AI client, inside their own Monte Carlo access.
-
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.
How to connect
How to connect Monte Carlo to Claude, ChatGPT or Cursor
Two steps, about a minute.
In Elaichi
Connect Monte Carlo once
-
Open Connections, choose Add connection, and pick Monte Carlo.
-
Optionally set Share with to give a team access, then press Connect.
-
Approve it in Monte Carlo. Monte Carlo'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.
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.
Monte Carlo 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.
Monte Carlo 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.
Monte Carlo 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 Monte Carlo 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.
Use cases
What teams do with Monte Carlo through Elaichi
Every one of these runs inside the access the person already has, and lands in the same audit log.
-
Data engineering
Work an alert before the morning standup
Ask what fired overnight in Monte Carlo, pull the details of the alert on the orders table, and get a summary ready before anyone else is awake.
-
Data platform
Trace a broken table back upstream
When a table goes stale, follow its lineage in Monte Carlo to find the upstream asset that stopped loading, without clicking through the graph by hand.
-
Analytics
Check a dashboard's source table is healthy
Before sending a report, ask whether the assets behind it have open alerts or failed monitors in Monte Carlo, and attach the answer to the email.
-
Data governance
Put a monitor on a key table
Describe the table and the check you want, and have a freshness or volume monitor created in Monte Carlo so the next gap is caught early.
-
Finance
Confirm revenue data is fresh before close
Ask whether the revenue and billing tables in Monte Carlo loaded on time this month and whether anything is still open before numbers go out.
-
Support
Explain why a stakeholder's numbers look wrong
When someone asks why a figure changed, pull the related Monte Carlo incidents and lineage and reply with a plain explanation in minutes.
Try asking
- “Which alerts fired on the orders table overnight?”
- “Show the upstream lineage for the revenue dashboard table.”
- “Create a freshness monitor on the customers table.”
Compare
Elaichi vs Zapier MCP vs Composio for Monte Carlo
All three can connect Monte Carlo to an AI assistant, and all three have admin controls. They differ in where access lives and how you pay.
| 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 Monte Carlo tools | Allow or restrict single Monte Carlo 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 Monte Carlo 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.
See it in Elaichi
What connecting Monte Carlo gets you
5 screens from the product, each doing one job for your Monte Carlo account.
The agent
Ask about data incidents in plain language.
Ask which Monte Carlo alerts fired overnight and get answers from live monitors and assets.
- alerts
- assets
- monitors
- incidents
Ask Elaichi to work across your apps.
Which alerts fired on the orders table overnight?
Show the upstream lineage for the revenue dashboard table.
Create a freshness monitor on the customers table.
Also runs in Claude, ChatGPT or Cursor
MCP clients
One endpoint, every client, no shared key.
Use Monte Carlo from Claude, ChatGPT or Cursor through one org endpoint over OAuth.
ElaichiMCP clientsClaude
ChatGPT
Cursor
Copy the endpoint
Toolboxes
Each team gets its own Monte Carlo toolbox.
Give data engineering, analytics and governance separate toolboxes, each scoped to that team.
- Data engineering
- Data platform
- Analytics
- Data governance
ElaichiToolboxesShared connections
Teammates investigate without ever seeing a credential.
One person connects Monte Carlo, shares it with teams, and nobody else touches a token.
- Data platform
- Analytics
- Finance data
- Marketing data
ElaichiConnectionsAudit log
Every Monte Carlo call answers who did what.
When, who, what happened and which monitor or asset, in an append-only log.
- When
- Who
- What happened
- Type
ElaichiAudit logLaunching 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 incident digest, you approve.
Monte Carlo alerts are fetched, grouped, drafted into a digest, approved, then posted back.
Monte Carlo digest
Run 418 · started 2 minutes ago · on behalf of Emily Carter
-
✓
Schedule
Every weekday at 8:00 AM
0.2s -
✓
Fetch alerts
Monte Carlo
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
Monte Carlo
Queued
Collections and dashboards
Monte Carlo health, computed without a model.
Four metrics, 14 days of alerts created and a team breakdown, refreshed on a schedule.
Monte Carlo health
Refreshed 4 minutes ago · every 15 minutes · from the alerts collection
Alerts
1,284 ↓ 12%
Assets
96 ↓ 8%
Needs attention
3 ↑ 2
Updated this week
412 ↑ 9%
Alerts created
Last 14 days
By team
Share of activity
Data platform 34%
Analytics 27%
Finance data 21%
Marketing data 18%
FAQ
Frequently asked questions
How do I connect Monte Carlo to Claude?
Connect Monte Carlo in Elaichi first: pick it from the catalog, sign in to your Monte Carlo account and approve the connection, with no client ID or secret to generate. Then in Claude go to Customize, then Connectors, then Add, and paste https://api.elaichi.ai/mcp as the address. Claude asks you to sign in to Elaichi, and Monte Carlo alerts, assets and monitors are available in your chats.
Does Monte Carlo work with ChatGPT and Cursor as well as Claude?
Yes. Once Monte Carlo 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 Monte Carlo once and each person signs in to Elaichi from whichever client they use.
What can an AI agent actually do with my Monte Carlo data?
An agent connected through Elaichi can review alerts and incidents in Monte Carlo, look up tables and other assets, follow lineage upstream and downstream, and create or update monitors. In practice that means asking what fired on the orders table overnight, which upstream asset caused it, and setting a freshness check so it is caught next time. Short, concrete asks tend to work better than long paragraphs.
Does connecting Monte Carlo give the AI everything in my workspace?
No. Every call to Monte Carlo runs as the person who signed in, so the agent sees only the assets, alerts and monitors that person can already see in Monte Carlo. Elaichi can narrow that further with restrictions and toolboxes, and it never widens what Monte Carlo itself allows.
Can I stop an agent from deleting or changing things in Monte Carlo?
Yes. Restrictions in Elaichi apply per action, so you can allow reading alerts and lineage in Monte Carlo while blocking the creation or removal of monitors. A restricted action is never advertised to Claude, ChatGPT or Cursor, so no prompt can reach it.
What happens to a Monte Carlo connection when someone leaves?
Offboarding a person in Elaichi ends their access to Monte Carlo through every client at once. A shared Monte Carlo connection keeps working for everyone else on the team. If you want to remove Monte Carlo entirely, disconnecting it once in Elaichi removes it from Claude, ChatGPT, Cursor and every other client.
Does the Monte Carlo MCP connector work with Gemini, Codex, Claude Code or other MCP clients?
Yes. Monte Carlo 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 Monte Carlo?
Yes. Both let Claude, ChatGPT or Cursor use Monte Carlo. 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 Monte Carlo call.
How is Elaichi different from Composio for Monte Carlo?
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 Monte Carlo: one address, restrictions per role or user, and $15 per user per month. Both have role permissions and a log of every call.
Put Monte Carlo in front of your team
14 days on Gold, no credit card. Connect it once and pick what each team can call.
- 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.