Connect AI agents to the Candid MCP server

Setup

1. Install the SDK

   • Node.js
   • Python

   npm install @scalekit-sdk/node dotenv

2. Set your credentials

   Add your Scalekit credentials to your .env file. Find values in app.scalekit.com > Developers > API Credentials.

   SCALEKIT_ENVIRONMENT_URL=<your-environment-url>
   SCALEKIT_CLIENT_ID=<your-client-id>
   SCALEKIT_CLIENT_SECRET=<your-client-secret>

3. Create the Candid MCP connection

   In AgentKit > Connections, create a Candid MCP connection. The name you give it is the connection_name your code passes. See Configure connections.

   Scalekit credentials are available for Candid MCP server, so you don't need to register an OAuth app.

4. Authorize a user and make your first call

   • Node.js
   • Python

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   import { ScalekitClient } from '@scalekit-sdk/node'
   2
   import 'dotenv/config'
   3
   import { createInterface } from 'node:readline/promises'
   4
   
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   const scalekit = new ScalekitClient(
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     process.env.SCALEKIT_ENVIRONMENT_URL,
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     process.env.SCALEKIT_CLIENT_ID,
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     process.env.SCALEKIT_CLIENT_SECRET,
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   )
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   const actions = scalekit.actions
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   const connector = 'candidmcp'
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   const identifier = 'user_123'
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   // Generate an authorization link for the user
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   const { link } = await actions.getAuthorizationLink({ connectionName: connector, identifier })
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   console.log('Authorize Candid MCP:', link)
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   const rl = createInterface({ input: process.stdin, output: process.stdout })
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   await rl.question('Press Enter after authorizing...')
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   rl.close()
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   // Make your first call
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   const result = await actions.executeTool({
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     connector,
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     identifier,
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     toolName: 'candidmcp_current_date',
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     toolInput: {},
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   })
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   console.log(result)

   npx tsx quickstart.mts

   Each user signs in once. See Authorize a user for the full flow and statuses.