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CocoIndex

Open-source incremental indexing framework that keeps agent context fresh with delta-only reprocessing

freeDR 57Open source and free to self-host; the site's calls to action are Get Started and Star on GitHub. An Enterprise page exists but no figures are published.View full pricing →

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cocoindex.io

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About CocoIndex

CocoIndex is an open-source incremental data framework for keeping AI agents supplied with fresh context. The core idea is delta processing: when a repository, document set, or note collection changes, only the changed portion is reindexed, which keeps freshness sub-second at any repo size instead of forcing a periodic full rebuild. Its flagship application is CocoIndex Code, an AST-based code-context layer that maintains call graphs, hierarchies, symbol tables, and semantic vector indexes over a codebase and keeps all of them current as commits land. That gives a coding or code-review agent structure rather than raw text — it can answer where a function is called from, trace blast radius before a change ships, and search by meaning rather than string match. Beyond code, the framework is general: published starters cover turning meeting notes into a knowledge graph of people, topics, decisions, and action items; walking N git repositories to produce LLM summaries plus a rolled-up organization overview; and real-time indexing pipelines into pgvector. Each starter is a handful of files and a flow declaration, which is the framework's main ergonomic claim — you define a flow, not a pipeline of glue scripts. It is aimed at developers building their own coding agents, code-review agents, and security-review agents who need an indexing substrate they control rather than a hosted black box.

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Key Features

✓Incremental processing — only the delta is reindexed, giving sub-second freshness

✓AST-based code context: call graphs, hierarchies, and symbol tables

✓Semantic search by meaning across a codebase rather than string matching

✓Blast-radius tracing of callers and callees before a change ships

✓Meeting-notes-to-knowledge-graph starter extracting people, topics, and decisions

✓Multi-repo LLM summaries rolled into an org-level overview

✓pgvector and tree-sitter integration

✓Flow-declaration model — each starter is a handful of files

CocoIndex Pros & Cons

✅ Pros

+Incremental-only reprocessing is a genuine cost and latency win over full reindexing
+AST awareness preserves function and class boundaries that naive chunking destroys
+Open source and self-hostable, so indexed code never leaves your infrastructure
+Working starters make it usable as a framework rather than a paper design