lindy-deploy-integration

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Deploy applications that integrate with Lindy AI agents. Use when deploying webhook receivers, callback handlers, or applications connected to Lindy agents. Trigger with phrases like "deploy lindy", "lindy deployment", "lindy production deploy", "release lindy integration".

AI & Automation 2,266 stars 315 forks Updated today MIT

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# Lindy Deploy Integration ## Overview Lindy agents run on Lindy's managed infrastructure. Deployment focuses on your **integration layer**: webhook receivers, callback handlers, and application code that Lindy agents interact with via HTTP Request actions and webhook triggers. ## Prerequisites - Lindy agents configured and tested - Application with webhook receiver endpoints - Deployment platform (Vercel, Railway, Docker, AWS, GCP) - Lindy API key and webhook secrets ## Instructions ### Step 1: Prepare Application for Deployment ```typescript // src/server.ts — Production-ready Lindy webhook receiver import express from 'express'; import helmet from 'helmet'; const app = express(); app.use(helmet()); app.use(express.json({ limit: '1mb' })); // Health check for load balancer app.get('/health', (req, res) => { res.json({ status: 'ok', timestamp: new Date().toISOString(), version: process.env.APP_VERSION || 'unknown', }); }); // Lindy webhook receiver with auth verification app.post('/lindy/callback', (req, res) => { const auth = req.headers.authorization; if (auth !== `Bearer ${process.env.LINDY_WEBHOOK_SECRET}`) { return res.status(401).json({ error: 'Unauthorized' }); } // Respond immediately, process async res.json({ received: true }); // Async processing processWebhook(req.body).catch(err => { console.error('Webhook processing error:', err); }); }); async function processWebhook(payload: any) { const { taskId, status, res...

Details

Author
jeremylongshore
Repository
jeremylongshore/claude-code-plugins-plus-skills
Created
7 months ago
Last Updated
today
Language
Python
License
MIT

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