Agent skill · Data & Analytics

neon-functions

Long-running, serverless Node.js HTTP functions deployed onto your Neon branch, with DATABASE_URL injected automatically and compute that runs next to your data. Use when a user wants to host an API, an AI agent with long streaming responses, a WebSocket or server-sent-events (SSE)...

Nick44,086★ · +407/wk · 1 repos on radarProfile →
claude-codecodexcursorMIT
Install
npx skills add sickn33/agentic-awesome-skills --skill neon-functions --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 7
SKILL.md size: 34 KB
Bundled scripts: none
Path: skills/neon-functions/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 44,414 · +328 this week
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Neon Functions This is a preview feature and only available in `us-east-2`. Neon Functions are long-running Node.js HTTP handlers deployed onto a Neon branch. Each function gets a public HTTPS URL, runs in the same region as your database, and — if the branch has Postgres — gets `DATABASE_URL` injected automatically. You deploy and manage them through the same Neon CLI, `neon.ts`, and API you already use. Use this skill to help the user define, run locally, deploy, and manage functions next to their database. Deliver a deployed function with its invocation URL, a working local `neon dev` loop, or a precise answer from the official Neon docs. ## When to Use Reach for Neon Functions when the workload is a request/response handler that benefits from staying alive and staying close to the data: - **Long-running request/response flows that outlast lambda-style limits.** Agents that make several LLM calls and tool invocations per request, or image/video generation, routinely blow past the ~10–60s execution caps and short streaming windows of traditional serverless functions. Neon Functions are long-running: the handler just needs to _start_ responding within 15 minutes, and an open str

What's inside
Steps it walks through
  1. When to Use
  2. What It Does
  3. Architecture: where Functions fit
  4. Setup
  5. Develop locally and deploy
  6. Neon Infrastructure as Code (neon.ts)
  7. Environment variables
  8. Connecting to Postgres
  9. WebSocket servers
  10. Heartbeat (keep the socket alive)
  11. Fan-out across isolates (do not skip this)
  12. Client must reconnect
  13. Server-sent events (SSE)
  14. MCP servers
Ships with 6 files
  • references/ai-sdk.md
  • references/hono-websockets.md
  • references/mastra-studio.md
  • references/mcp.md
  • references/sentry.md
  • references/sse.md
Commands it runs
neon dev      # serves every function in neon.ts with hot reload; injects DATABASE_URL & friends
neon deploy   # bundles with esbuild, uploads, and applies neon.ts to the linked branch
neon config status   # print the branch's live config (deployed functions)
neon config plan     # dry-run diff of what apply would change
neon config apply    # bundle + deploy the declared functions  (neon deploy is an alias)
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About this skill
What does the neon-functions skill do?

Long-running, serverless Node.js HTTP functions deployed onto your Neon branch, with DATABASE_URL injected automatically and compute that runs next to your data. Use when a user wants to host an API, an AI agent with long streaming responses, a WebSocket or server-sent-events (SSE)...

How do I install it?

Run `npx skills add sickn33/agentic-awesome-skills --skill neon-functions --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From sickn33/agentic-awesome-skills, a repository with 44,414 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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