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<a href="https://www.npmjs.com/package/agentpond"><img src="https://img.shields.io/node/v/agentpond.svg" alt="Node.js version"></a>
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</p>
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AgentPond is a lightweight trace backend and CLI for AI applications. It keeps raw traces in object storage you control and syncs them into a local DuckDB cache for fast analysis by developers and coding agents. Use it with Firebase Storage, Supabase Storage, Amazon S3, Google Cloud Storage, Vercel Blob, or custom infrastructure. Firebase, Supabase, and Vercel include automated setup; other deployments use the manual setup path.
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AgentPond is a lightweight trace backend and CLI for AI applications. It keeps raw traces in object storage you control and syncs them into a local DuckDB cache for fast analysis by your coding agent. Use it with Firebase Storage, Supabase Storage, Amazon S3, Google Cloud Storage, Vercel Blob, or custom infrastructure. Firebase, Supabase, and Vercel projects include automated setup; other deployments use a manual setup path.
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## How it works
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## Getting started
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Start with the [Manual deployment setup](./docs/getting-started/manual-setup.md) to choose a write path, configure object storage, instrument the application, and sync its traces into AgentPond.
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Start with the [Manual deployment setup](./docs/getting-started/manual-setup.md) to configure object storage, instrument the application, and sync its traces into AgentPond.
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For Firebase, Supabase, and Vercel, AgentPond also provides automated quick starts:
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For Firebase, Supabase, and Vercel projects, AgentPond provides automated quick starts:
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- [Firebase quick start](./docs/getting-started/firebase.md)
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- [Supabase quick start](./docs/getting-started/supabase.md)
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- [Vercel quick start](./docs/getting-started/vercel.md)
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All require Node.js 22 or newer for the CLI. From the provider project, run:
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All require Node.js 22 or newer for the CLI. From your project folder, run:
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```sh
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npx agentpond init
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```
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The command detects the platform, installs AgentPond's instrumentation and analytics skills, and prints a prompt for your coding agent. The agent inspects the trusted Node.js application, proposes the provider-specific setup, implements it after confirmation, and verifies a real trace.
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The command detects the platform, installs AgentPond's instrumentation and analytics skills, and prints a install prompt for your coding agent. Your agent inspects then the application, proposes a setup, implements it after confirmation, and verifies a real trace end to end.
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Once the application has emitted a trace:
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