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cocoindex-io/cocoindex

Incremental engine for long horizon agents 🌟 Star if you like it

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Official descriptionrprise-hero-light.svg"> <img src="cocoindex.io alt="Enterprise corpus — codebase, Slack, meeting notes, and documentation — flowing continuously through the CocoIndex incremental sync engine into a production AI agent with always-fresh context.

Star count: 11,710 ★ · cocoindex-io/cocoindex · read from the GitHub search API · (checked 2026-10-16 20:00:20)
Source: read directly from its GitHub page · type: open-source project
Harvest history: first seen 2026-10-15 · last seen 2026-10-16 · seen 2× · listed by 1 sources
Score: score 126 · 11,710 ★ · 1 sources · repo

FAQ (answers come from our records)

How do I install it?

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repository cocoindex-io/cocoindex；first catalogued 2026-10-15；last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.

Third-party quality signals

Your agents deserve fresh context.

以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →

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CocoIndex turns codebases, meeting notes, inboxes, Slack, PDFs, and videos into live, continuously fresh context for your AI agents and LLM apps to reason over effectively — with minimal incremental processing. Get your production AI agent ready in 10 minutes with reliable, continuously fresh data — no stale batches, no context gap
Incremental · only the delta  ·  Any scale · parallel by default  ·  Declarative · Python, 5 min
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Built with CocoIndex ❤️
See all 20+ examples · updated every week →
Get started
Declare *what* should be in your target — CocoIndex keeps it in sync forever, recomputing only the Δ.
Run once to backfill. Re-run anytime — only the changed files re-embed.
Building with an AI coding agent?
Drop in our CocoIndex skill so your agent writes correct v1 code — concepts, APIs, patterns, all in one file.
See Use with AI coding agents for install steps.
  
React — for data engineering
See the React ↔ CocoIndex mental model →
Incremental engine for long-horizon agents
Data transformation for any engineer, designed for AI workloads —
with a smart incremental engine for always-fresh, explainable data.
Why incremental?
Your agents are only as good as the data they see. Batch pipelines drift stale. CocoIndex stays live — and only runs the Δ.
What can you build?
See all 20+ examples · updated every week →
Working starters from the examples tree — clone, plug your source, ship.
Building something with CocoIndex? We want to see it. Tag @cocoindex_io on X or drop a link in #showcase on Discord. We'll boost it. 🥥
Community
We are so excited to meet you.
Every typo fix, new connector, doc tweak, or full-on rewrite makes CocoIndex better.
Come hang out — big PRs and small ones, both welcome.
📝 Read the contributing guide  · 
🐛 good first issues  · 
💬 Say hi on Discord
CocoIndex Enterprise
Large corpus — built for enterprise scale.
Incremental compute is the only way to keep large corpora fresh without re-embedding them every cycle.
CocoIndex scales from a single repo to petabyte-scale stores — parallel by default, delta-only by design.
Process once. Reconcile forever.
When a source changes, CocoIndex identifies the affected records, propagates the change
across joins and lookups, updates the target, and retires stale rows —