Every session starts from zero
Yesterday’s findings are gone. The agent re-reads the same sources, re-derives the same conclusions, and bills you twice.
Use case · Research agents
LeanCTX gives research agents persistent, citable memory: findings land in a knowledge store with provenance, the EvidenceLedger keeps verbatim quotes with sources, and cached re-reads cost ~13 tokens. Your agent collects once, remembers across sessions, and answers with citations instead of re-crawling.
Same engine. Different workflow. Always the right context.
Yesterday’s findings are gone. The agent re-reads the same sources, re-derives the same conclusions, and bills you twice.
A summary without sources is a liability. Research output needs verbatim quotes with provenance.
Twenty open PDFs do not fit in a context window. Agents need ranked recall of what matters, not everything at once.
Everything below ships in the open-source binary today. No roadmap items, no waitlists.
verbatim quotes with source attribution, ready to cite
findings, decisions and blockers persist across sessions
sources collapse into attributable units
meaning-based retrieval over everything collected
revisiting a known source is nearly free
$ ctx_url_read("https://arxiv.org/abs/2310.08560", mode="quotes")$ lean-ctx knowledge remember "accuracy falls 98→64% with window noise" --category discovery --key context-rot$ lean-ctx knowledge recall "context rot"$ ctx_semantic_search("why does accuracy fall with window size")Sessions, knowledge categories and recall.
Learn moreFrom sources to a cited answer.
Learn moreWhat persists, where, and how to query it.
Learn morectx_knowledge, ctx_semantic_search and friends.
Learn moreThe EvidenceLedger stores verbatim quotes with their source URL or file. Answers can reference evidence IDs, so every claim traces back to an original you can open.
Yes. Findings live in a local knowledge store with categories (discovery, decision, blocker…) and are restored into every new session automatically.
Collected sources are deduplicated, compressed and indexed with BM25 plus a knowledge graph. Recall returns ranked, budgeted context, never the whole corpus at once.
Free for local use, forever. CI enforces it. One binary, ten minutes to the first measured gain.
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