Make MCP

Live

API KEY

AUTOMATION

Automation

Every workflow, automation scenario, and integration your team builds lives in Make. Make MCP gives your agent authenticated access to automation data scoped to the user who authorized it.

  • Acts as the user: Access and write actions stay tied to the Make MCP account that authorized the agent.
  • Credentials stay vaulted: AES-256, resolved at request time, never in LLM context.
  • Scoped before every call: User permissions enforced. 90-day audit trail.
Make MCP
agent · Acme Q3
Run
Which scenarios failed in the last 24 hours and what were the error messages?
S
make_executions_list
79ms
Automation agent
3 scenario failures in 24h. CRM-Sync-HubSpot (2 failures, 'Rate limit exceeded at module 4'), Slack-Digest (1 failure, 'OAuth token expired at module 2'), Invoice-Generator (1 failure, 'PDF template missing').
Sources: 3 failed scenarios, last 24h
makemcpmcp
3 scenarios
18:29
Message Claude...

Tools your automation agent reaches for on Make MCP, scoped per user.

CALL ANY TOOL
List and run scenarios, retrieve execution history, and debug failures with detailed logs.
makemcp_app_documentation_get
Get app documentation
Retrieves markdown documentation for the specific Make App. Use when configuring Make Apps and Modules and when you need to learn more about the available capabilities.
Parameters
Name
Type
Required
Description
appName
string
Required
Name of the App to get the documentation for.
makemcp_app-modules_list
List app-modules
makemcp_apps_recommend
Apps recommend
makemcp_credential-requests_create
Create credential-requests
makemcp_credential-requests_credential-delete
Credential-requests credential-delete
makemcp_credential-requests_list-app-modules-with-creds
Credential-requests list-app-modules-with-creds
makemcp_custom_apps_connections_fetch
Fetch custom apps connections
makemcp_custom_apps_functions_get_code
Custom apps functions get code
makemcp_custom_apps_functions_set_code
Custom apps functions set code
makemcp_custom_apps_rpcs_delete
Delete custom apps rpcs
makemcp_custom_apps_update
Update custom apps
makemcp_custom-apps_changes-fetch
Custom-apps changes-fetch
makemcp_custom-apps_connections-configure
Custom-apps connections-configure
makemcp_custom-apps_functions-create
Custom-apps functions-create
makemcp_custom-apps_functions-set-code
Custom-apps functions-set-code
makemcp_custom-apps_get-example
Custom-apps get-example
makemcp_custom-apps_rpcs-delete
Custom-apps rpcs-delete
makemcp_data-structures_update
Update data-structures
makemcp_enums_timezones
Enums timezones
makemcp_executions_list
List executions
makemcp_hook-metadata_get
Get hook-metadata
makemcp_hooks_create
Create hooks
makemcp_hooks_delete
Delete hooks
makemcp_hooks_learn_start
Start hooks learn
makemcp_hooks_learn_stop
Stop hooks learn
makemcp_public-templates_get
Get public-templates
makemcp_public-templates_list
List public-templates
makemcp_rpc_execute
Execute rpc
makemcp_scenarios_run
Run scenarios
makemcp_show_execution_result
Show execution result

For more tools, view docs.

Build your Agent
Drop the toolkit in, point it at the user, and your automation agent can use Make MCP from the first run.
Python · LlamaIndex
import { ScalekitClient } from "@scalekit-sdk/node";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { z } from "zod";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["makemcp"], toolNames: ["make_scenarios_list", "make_scenario_get", "make_scenario_run"] },
pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
name: t.tool.definition.name,
description: t.tool.definition.description,
schema: z.object({}).passthrough(),
func: async (args) => {
const { data } = await sk.tools.executeTool({
toolName: t.tool.definition.name,
identifier: "user_123",
params: args,
});
return JSON.stringify(data);
},
}));

const agent = createReactAgent({ llm, tools: lcTools });
import { ScalekitClient } from "@scalekit-sdk/node";
import OpenAI from "openai";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["makemcp"], toolNames: ["make_scenarios_list", "make_scenario_get", "make_scenario_run"] },
pageSize: 100,
});

const llmTools = tools.map((t) => ({
type: "function",
function: {
name: t.tool.definition.name,
description: t.tool.definition.description,
parameters: t.tool.definition.input_schema,
},
}));

const resp = await openai.responses.create({
model: "gpt-4o", input: prompt, tools: llmTools,
});
import { ScalekitClient } from "@scalekit-sdk/node";
import Anthropic from "@anthropic-ai/sdk";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["makemcp"], toolNames: ["make_scenarios_list", "make_scenario_get", "make_scenario_run"] },
pageSize: 100,
});

const llmTools = tools.map((t) => ({
name: t.tool.definition.name,
description: t.tool.definition.description,
input_schema: t.tool.definition.input_schema,
}));

const msg = await anthropic.messages.create({
model: "claude-sonnet-4-6", max_tokens: 1024,
tools: llmTools,
messages: [{ role: "user", content: prompt }],
});
import { Agent } from "@google/adk/agents";
import {
MCPToolset, StreamableHTTPConnectionParams,
} from "@google/adk/tools/mcp";

const toolset = new MCPToolset({
connectionParams: new StreamableHTTPConnectionParams({
url: "https://mcp.scalekit.com/makemcp",
headers: { Authorization: `Bearer ${userScopedToken}` },
}),
});

const agent = new Agent({
name: "agent", model: "gemini-2.0-flash",
tools: await toolset.getTools(),
});
Try these prompts
Paste any prompt into your agent to start using Make MCP.
Scenarios & status
Copy the prompt
Copied
List all active scenarios.
Copy the prompt
Copied
Get details for [scenario name].
Copy the prompt
Copied
Which scenarios failed in the last 24 hours?
Copy the prompt
Copied
List scenarios in [team].
Runs & logs
Copy the prompt
Copied
Run [scenario name].
Copy the prompt
Copied
List last 10 executions of [scenario].
Copy the prompt
Copied
Get logs for execution [id].
Copy the prompt
Copied
Which executions took over 60 seconds?
Reporting
Copy the prompt
Copied
Total executions this month.
Copy the prompt
Copied
Error rate by scenario.
Copy the prompt
Copied
Which scenarios run most frequently?
Copy the prompt
Copied
Scenarios with no executions in 7 days.
SEE HOW AUTH WORKS
Users authorize Make MCP once. Their credentials stay vaulted, every call is checked, and every action is logged.
1
Authorize
Your user connects
Make MCP
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
Limited to user
2
Store
Their
Make MCP
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
Make MCP
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
Make MCP
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
Same per-user auth pattern across other automation agents and MCP connectors. Working code, live demos, fork what fits.
Engineering Teams
Slack triage
Polls Slack for new messages, classifies bugs and support requests with a LangGraph router, files GitHub issues or Zendesk tickets, and confirms in the thread.
Support and Ops Teams
Support ticket automation agent
Fetches new Zendesk tickets, drafts a reply from Notion knowledge base articles, digests what it cannot answer to Slack, and archives the rest, acting as the support agent rather than a shared API key.
Engineering Teams
DevOps assistant agent
Polls GitHub for failing checks and stale PRs, opens Linear issues for the ones that need work, and posts a daily digest to Slack. It acts as the engineer, not a shared service account.
Support and Ops Teams
Email-to-calendar agent
Reads scheduling intent out of Gmail threads, resolves the times everyone actually has free, and creates the event on the user's own Google Calendar. No shared service account.
Test other agents
Same per-user auth pattern across other automation agents and MCP connectors. Working code, live demos, fork what fits.
ENGINEERING
DevOps assistant agent
Poll GitHub for failing checks and stale pull requests, open Linear issues for the ones that need work, and digest to Slack.
ENGINEERING
Slack triage agent
Classify new Slack messages as bugs or support requests, file the GitHub issue or Zendesk ticket, and reply in the thread.
SUPPORT
Support ticket automation (Google ADK)
Fetch, annotate, and archive Zendesk tickets with Notion context, digesting anything it cannot answer to Slack.
OPS
Email-to-calendar scheduling agent
Read scheduling intent out of Gmail threads, resolve mutual free time, and create the Google Calendar event.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
01.
Shared tokens break per-user analytics
A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential so attribution, audit, and scope stay accurate.
// shared token
 audit → bot_service_account
 user_filter → broken

 // scalekit
 audit → user_abc
 scope → enforced ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
Make MCP today. Others tomorrow.
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
FAQs
Frequently Asked Questions
Does the agent access Make MCP as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.
Where is the Make MCP api key stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.
Can I limit what the agent is allowed to do in Make MCP?
Yes. Pass a tool name filter to listScopedTools so the automation agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Make MCP.
What happens when a user revokes Make MCP access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.
Can the agent trigger scenarios in other Make organizations the user has access to?
One organization per API key. The key is scoped to the Make organization that generated it. Cross-organization scenario access requires a separate connected account and key per org.
Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""makemcp"": {
""url"": ""https://mcp.scalekit.com/makemcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.makemcp]
url = ""https://mcp.scalekit.com/makemcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""makemcp"": {
""url"": ""https://mcp.scalekit.com/makemcp"",
""type"": ""http""
}
}
}