Jeremylongshore Claude Code Plugins Plus Skills Exa Deploy Integration

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

// 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 }
    );
  }
}

# Deploy to Vercel
vercel env add EXA_API_KEY production
vercel --prod

Step 2: Docker Deployment

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"]

// 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

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

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

Resources

• Exa API Documentation
• exa-js SDK
• Vercel Edge Functions

Next Steps

For multi-environment setup, see exa-multi-env-setup. For production checklist, see exa-prod-checklist.

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