Parlel gives AI coding agents instant, sandboxed access to 250+ services like databases, queues, cloud providers, and SaaS APIs through simple markdown references they can fetch and use directly. Each service runs as a lightweight microservice, starts in seconds, and uses ~1 MB of memory, making it practical to create isolated environments for every agent, branch, test, or experiment without the overhead of full infrastructure.
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Maker
š
Hey Product Hunt š
I'm Dheeraj, the creator of Parlel.
The idea came from watching AI coding agents struggle with local infrastructure. Every time an agent needed Redis, Postgres, S3, Stripe, or another dependency, the options were either:
⢠Run real services locally (heavy and expensive)
⢠Spin up Docker containers (slow and resource intensive)
⢠Mock everything (often unrealistic)
This gets even worse when you want multiple agents working in parallel, each with its own isolated environment.
So I built Parlel.
Parlel provides 250+ lightweight service emulators that AI agents can interact with directly through simple markdown references. Each service starts instantly and uses roughly 1 MB of memory, making it practical to create isolated environments for every agent, branch, test run, or experiment.
Our goal is simple: make infrastructure effectively free for AI agents.
I'd love to hear:
* What services would you want your coding agents to access?
* What's the biggest bottleneck in your current AI development workflow?
Happy to answer questions and would love your feedback š