exa-deploy-integration
Deploy Exa integrations to Vercel, Docker, and Cloud Run platforms. Use when deploying Exa-powered applications to production, configuring platform-specific secrets, or building search API endpoints. Trigger with phrases like "deploy exa", "exa Vercel", "exa production deploy", "exa Cloud Run", "exa Docker".
Best use case
exa-deploy-integration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Deploy Exa integrations to Vercel, Docker, and Cloud Run platforms. Use when deploying Exa-powered applications to production, configuring platform-specific secrets, or building search API endpoints. Trigger with phrases like "deploy exa", "exa Vercel", "exa production deploy", "exa Cloud Run", "exa Docker".
Teams using exa-deploy-integration should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/exa-deploy-integration/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How exa-deploy-integration Compares
| Feature / Agent | exa-deploy-integration | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Deploy Exa integrations to Vercel, Docker, and Cloud Run platforms. Use when deploying Exa-powered applications to production, configuring platform-specific secrets, or building search API endpoints. Trigger with phrases like "deploy exa", "exa Vercel", "exa production deploy", "exa Cloud Run", "exa Docker".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Exa Deploy Integration
## Overview
Deploy applications using Exa's neural search API to production. Covers API endpoint creation, secret management per platform, caching for production traffic, and health check endpoints.
## Prerequisites
- Exa API key stored in `EXA_API_KEY` environment variable
- Application using `exa-js` SDK
- Platform CLI installed (vercel, docker, or gcloud)
## Instructions
### Step 1: Vercel Edge Function
```typescript
// api/search.ts — Vercel API route
import Exa from "exa-js";
export const config = { runtime: "edge" };
export default async function handler(req: Request) {
if (req.method !== "POST") {
return new Response("Method not allowed", { status: 405 });
}
const exa = new Exa(process.env.EXA_API_KEY!);
const { query, numResults = 5 } = await req.json();
if (!query || typeof query !== "string") {
return Response.json({ error: "query is required" }, { status: 400 });
}
try {
const results = await exa.searchAndContents(query, {
type: "auto",
numResults: Math.min(numResults, 20),
text: { maxCharacters: 1000 },
highlights: { maxCharacters: 300, query },
});
return Response.json({
results: results.results.map(r => ({
title: r.title,
url: r.url,
score: r.score,
snippet: r.text?.substring(0, 300),
highlights: r.highlights,
})),
});
} catch (err: any) {
const status = err.status || 500;
return Response.json(
{ error: err.message, requestId: err.requestId },
{ status }
);
}
}
```
```bash
# Deploy to Vercel
vercel env add EXA_API_KEY production
vercel --prod
```
### Step 2: Docker Deployment
```dockerfile
FROM node:20-slim
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
RUN npm run build
EXPOSE 3000
CMD ["node", "dist/index.js"]
```
```typescript
// src/server.ts — Express search API
import express from "express";
import Exa from "exa-js";
const app = express();
app.use(express.json());
const exa = new Exa(process.env.EXA_API_KEY!);
app.post("/api/search", async (req, res) => {
const { query, numResults = 5, type = "auto" } = req.body;
try {
const results = await exa.searchAndContents(query, {
type,
numResults,
text: { maxCharacters: 1000 },
});
res.json(results);
} catch (err: any) {
res.status(err.status || 500).json({ error: err.message });
}
});
app.get("/health", async (_req, res) => {
try {
await exa.search("health", { numResults: 1 });
res.json({ status: "healthy", service: "exa" });
} catch {
res.status(503).json({ status: "unhealthy", service: "exa" });
}
});
app.listen(3000, () => console.log("Listening on :3000"));
```
### Step 3: Google Cloud Run
```bash
set -euo pipefail
# Store API key in Secret Manager
echo -n "$EXA_API_KEY" | gcloud secrets create exa-api-key --data-file=-
# Deploy with secret mounted as env var
gcloud run deploy exa-search-api \
--source . \
--set-secrets=EXA_API_KEY=exa-api-key:latest \
--allow-unauthenticated \
--region us-central1
```
### Step 4: Production Search with Redis Cache
```typescript
import Exa from "exa-js";
import { Redis } from "ioredis";
import { createHash } from "crypto";
const exa = new Exa(process.env.EXA_API_KEY!);
const redis = new Redis(process.env.REDIS_URL!);
async function cachedSearch(query: string, opts: any = {}, ttl = 3600) {
const key = `exa:${createHash("sha256").update(JSON.stringify({ query, ...opts })).digest("hex")}`;
const cached = await redis.get(key);
if (cached) return JSON.parse(cached);
const results = await exa.searchAndContents(query, {
type: "auto",
numResults: 5,
text: { maxCharacters: 1000 },
...opts,
});
await redis.set(key, JSON.stringify(results), "EX", ttl);
return results;
}
```
## Error Handling
| Issue | Cause | Solution |
|-------|-------|----------|
| 401 in production | API key not set | Verify env var in deployment platform |
| Rate limited | Too many requests | Implement Redis cache + request queue |
| Slow responses | Large content requests | Reduce `maxCharacters` or `numResults` |
| Timeout on Edge | Query too complex | Use `type: "fast"` for edge functions |
| Cold start latency | Serverless cold start | Keep Exa client initialization outside handler |
## Resources
- [Exa API Documentation](https://docs.exa.ai)
- [exa-js SDK](https://github.com/exa-labs/exa-js)
- [Vercel Edge Functions](https://vercel.com/docs/functions/edge-functions)
## Next Steps
For multi-environment setup, see `exa-multi-env-setup`. For production checklist, see `exa-prod-checklist`.Related Skills
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