Control Plane MCP connector
The Control Plane connector lets Claude, ChatGPT, Cursor, or any MCP client list, deploy, diagnose, restart, roll back and promote workloads across your GVCs and locations, as the signed-in person, with every call logged in Elaichi.
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How it connects. Connects over OAuth. 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 Control Plane to Claude, ChatGPT or Cursor
Two steps, about a minute.
In Elaichi
Connect Control Plane once
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Open Connections, choose Add connection, and pick Control Plane.
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Optionally set Share with to give a team access, then press Connect.
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Approve it in Control Plane. Control Plane'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.
Control Plane MCP connector for 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.
Control Plane MCP connector for 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.
Control Plane MCP connector for 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 Control Plane 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 Control Plane 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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Platform
Stand up a new environment for a team
Describe the environment in plain words, and the agent creates the GVC, adds the locations it should run in, and deploys the first workload. The setup follows the Control Plane rules your organization already has in place.
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Engineering
Ship a build and confirm it landed
Deploy an app to Control Plane from the chat you are already in, then ask whether the workload is healthy before telling the rest of the team.
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On-call
Diagnose a failing workload at 2am
Ask what is wrong with a workload, restart it, or roll it back to the last good version without opening the Control Plane console. The agent only touches what your own Control Plane access allows.
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Release management
Promote a workload from staging to production
Once a release has settled in staging, ask the agent to promote the workload and add a database if the new version needs one. Each step is written to the audit log with your name on it.
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Security
Review who and what can reach a resource
Pull the permissions on any Control Plane resource, check which workloads are allowed to talk to each other, and grant cloud access only where it has been approved.
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Developer experience
Answer platform questions straight from the docs
New engineers can search Control Plane documentation, rules and resource schemas in plain language, so the platform team stops answering the same question every week.
Try asking
- “Diagnose the checkout workload in the production GVC”
- “Roll back the api workload to the previous version”
- “Add the aws-eu-central-1 location to the staging GVC”
Compare
Elaichi vs Zapier MCP vs Composio for Control Plane
All three can connect Control Plane 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 Control Plane tools | Allow or restrict single Control Plane 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 Control Plane 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
Control Plane tools for your AI agents
119 tools are ready to call through Elaichi's MCP endpoint the moment you connect Control Plane, governed by the same roles, restrictions, and audit log as everything else in Elaichi. Control Plane builds and runs these tools.
No tools match your search.
See it in Elaichi
What connecting Control Plane gets you
6 screens from the product, each doing one job for your Control Plane account.
The agent
Ask about your workloads in plain language.
Three starter prompts pull live answers from Control Plane workloads, GVCs and locations.
- workloads
- gvcs
- locations
- databases
Ask Elaichi to work across your apps.
Diagnose the checkout workload in the production GVC
Roll back the api workload to the previous version
Add the aws-eu-central-1 location to the staging GVC
Also runs in Claude, ChatGPT or Cursor
MCP clients
One endpoint connects Control Plane to every client.
Claude, ChatGPT and Cursor reach Control Plane through one governed endpoint, no SDK, no shared key.
Copy the endpoint
Tool catalog
119 Control Plane tools, ready without code.
Workloads, GVCs, locations, databases and permissions, cataloged and callable with no custom code.
- Get cpln rules
- Get cpln skill
- Plan app
- Get resource schema
Toolboxes
Every team gets its own Control Plane toolbox.
Platform deploys and promotes, on-call diagnoses and restarts, each from a toolbox scoped to them.
- Platform
- Engineering
- On-call
- Security
Shared connections
Teammates deploy without ever holding a credential.
One person connects Control Plane, shares it with teams, and the sign-in stays with them.
- Platform
- Production
- Staging
- On-call
Audit log
Every rollback is logged with a name.
When, who, what happened and which workload, kept in an append-only log.
- 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 starts the work, a person approves.
Workload health is fetched, grouped and drafted into a digest, approved, then posted to Control Plane.
Control Plane digest
Run 418 · started 2 minutes ago · on behalf of Emily Carter
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✓
Schedule
Every weekday at 8:00 AM
0.2s -
✓
Fetch workloads
Control Plane
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
Control Plane
Queued
Collections and dashboards
Workload health reported without asking anyone.
Four metrics and 14 days of workloads created, computed on a schedule with no model.
Control Plane health
Refreshed 4 minutes ago · every 15 minutes · from the workloads collection
Workloads
1,284 ↓ 12%
Gvcs
96 ↓ 8%
Needs attention
3 ↑ 2
Updated this week
412 ↑ 9%
Workloads created
Last 14 days
By team
Share of activity
Platform 34%
Production 27%
Staging 21%
On-call 18%
FAQ
Frequently asked questions
How do I connect Control Plane to Claude?
Two steps. In Elaichi, add the Control Plane connector and sign in to your Control Plane organization in the browser window that opens, approving the connection as yourself over OAuth. Then in Claude, open Customize, then Connectors, then Add, and paste https://api.elaichi.ai/mcp. There is no OAuth application to register and no client ID or secret to generate.
Does Control Plane work with ChatGPT and Cursor as well as Claude?
Yes. Once Control Plane 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 Control Plane once and every client you use picks it up.
What can an AI agent actually do with my Control Plane data?
With Control Plane connected, an agent can list and read your workloads, GVCs, locations and other resources, deploy an app, add a database, and diagnose, restart, roll back or promote a workload. It can also look up permissions, review which workloads can reach each other, and search Control Plane documentation and rules. Short, concrete asks such as "restart the checkout workload in production" work better than long sentences.
Does connecting Control Plane give the AI my whole organization?
No. Every call to Control Plane runs as the person who signed in, so the agent sees only the GVCs, workloads and resources that person can already see in Control Plane. Elaichi can narrow that access further with roles and restrictions, and it can never widen it beyond what Control Plane itself allows.
Can I stop an agent from deleting or changing things in Control Plane?
Yes. Restrictions in Elaichi apply per action, so you can allow reading and diagnosing Control Plane workloads while blocking deletes, rollbacks or changes to GVC locations. A restricted action is never advertised to Claude, ChatGPT, Cursor or any other client, so no prompt can reach it.
What happens to a Control Plane connection when someone leaves?
Offboarding a person in Elaichi ends their access to Control Plane through every client at once. A Control Plane connection they shared keeps working for everyone else on the team. Disconnecting Control Plane once in Elaichi removes it from Claude, ChatGPT, Cursor and every other client together.
Does the Control Plane MCP connector work with Gemini, Codex, Claude Code or other MCP clients?
Yes. Control Plane 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 Control Plane?
Yes. Both let Claude, ChatGPT or Cursor use Control Plane. 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 Control Plane call.
How is Elaichi different from Composio for Control Plane?
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 Control Plane: one address, restrictions per role or user, and $15 per user per month. Both have role permissions and a log of every call.
Put Control Plane in front of your team
14 days on Gold, no credit card. Connect it once and pick what each team can call.
- Works with
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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.