I’m a developer. I’ve been scaffolding and wiring up MCP servers manually for months — scaffold locally, write tests, catch the edge cases I missed, rewrite, test against a separate MCP client, write the CI config, debug the CI config, publish. That’s a solid 2–3 days of focused engineering work per server. I was curious if an agent could do it better. So I built a “Project Developer” agent inside Hyperagent. Its job: take a brief, scaffold a TypeScript MCP server from scratch, implement the tools, test everything, and ship to npm with working CI/CD. I connected it to my GitHub via a protected skill workflow — the key is stored outside the chat, never injected into a session. I gave it four standing rules: Run the full MCP test suite after every code change. No exceptions. Enforce TypeScript strict mode. Validate all API responses against Zod schemas. Commit with semantic versioning after every passing test run. After every push: generate a markdown report of test coverage, lint status, and build health. Then I kicked it off. Here’s what happened: The agent scaffolded the project — TypeScript, esbuild, vitest, lint-staged — and got to work. It hit the first real wall about 20 minutes in: our internal API uses a custom auth header that isn’t well documented. Instead of guessing and burning through credits, it paused and asked me one specific multiple-choice question about the auth flow. I answered. It kept going. By hour 2, it had three core MCP tools implemented and passing: query_resource , validate_payload , and sync_batch . Clean conventional commit. Pushed to a feature branch via the native Git integration. I came back at hour 4. The agent had already spun up subagents — one handling the integration testing layer, another working the npm packaging and README in parallel. The subagent flagged something I hadn’t asked it to look for: a race condition in sync_batch that unit tests don’t catch. It reported back to the primary agent, which patched the bug, regenerated the lockfile, launched another subagent to harden the test infrastructure, and re-ran the full suite. 47 tests. All green. I didn’t touch anything. The CI/CD workflow came next — GitHub Actions, automated testing across Node 18/20/22, version-tag publish job. Written from scratch, no template. Another clean commit. I went to lunch. Hour 7: I came back and it was still running. The full MCP server was live inside the agent’s VM, executing final integration tests against itself. Then it did something I hadn’t asked for: it generated a skill file documenting the architecture, API patterns, and a troubleshooting guide — and saved it directly to Hyperagent’s skills integration. Reusable on every future MCP project. It built its own institutional memory. Final numbers: Test coverage: 94% Bundle size: 42KB Lint errors: 0 Agent runtime: 7 hours, 23 minutes My active time: ~8 minutes Total cost: $52.40 (Claude Opus 4.6) The race condition catch alone was worth it. That’s exactly the kind of bug that makes it into production and stays quiet until it isn’t quiet anymore. The part I keep coming back to: the agent didn’t just write code. It reasoned about architecture, caught a concurrency bug I would have shipped, and generated a reusable skill so the next MCP project starts with a head start. My previous version of this workflow was 2–3 days. This was 8 minutes of my time and $52. If you want to try it yourself, the link in my profile gets you $1,000 in Hyperagent credits to start building. Has anyone else used agents for serious backend work? What’s the most complex thing you’ve handed off? https://preview.redd.it/17ng3ojtt43h1.png?width=1344&format=png&auto=webp&s=78721d9e65e4dce130da463873d12869cc74f6dd submitted by /u/Smart_War3981
Originally posted by u/Smart_War3981 on r/ArtificialInteligence