LeanCTX

The Context SDK for AI Agents. Give every agent a context system.

LeanCTX is a local context layer for existing AI agents. It selects, shapes, reuses, and recovers the project context an agent needs inside the agent loop you own. Your agent, model, tools, and task logic remain yours.

Your framework runs the agent. LeanCTX manages the context path routed through it.

LeanCTX supports three ways to integrate:

• Attach — Available — add LeanCTX around a supported coding agent through CLI, MCP, or a local proxy.
• Wrap — Preview — use the declared Python SDK v1 reference-wrapper path with an explicit lifecycle and evidence boundary.
• Embed — Preview — integrate the Context Engine inside a custom host; the host keeps ownership of its full agent loop.

It is not an agent platform, a generic agent builder, a hosted execution service, or a marketplace.

What is available now

• Local Runtime, CLI, MCP, and local proxy paths.
• Context selection, structural views, compression, reuse, and recovery.
• Supported local setup paths for Codex, Claude Code, and Cursor.
• Local Receipt/evidence primitives and offline verification.

The Python SDK v1 and its declared OpenAI Agents reference-wrapper are Preview. Performance Profiles, first-class Context Kits, the Performance Benchmark product flow, AutoTune, public rankings, and organization-scale operation are Research. An implementation directory is not a product claim. Local agent-presence, handoff, and related coordination substrate are also Research; LeanCTX does not currently provide a public multi-agent orchestration contract.

The context lifecycle

Select → Shape → Reuse → Recover

Evidence is a separate proof discipline: a gain is valid only with a comparable baseline and treatment, a declared quality threshold, and visible methodology. A lower token count or calculated cost is not a successful outcome on its own.

Install

# Pick one installation method.
curl -fsSL https://leanctx.com/install.sh | sh
brew tap yvgude/lean-ctx && brew install lean-ctx
npm install -g lean-ctx-bin
cargo install lean-ctx

# Connect one supported agent, then verify the local installation.
lean-ctx wrap codex
lean-ctx doctor

Use lean-ctx unwrap codex to remove that integration, or lean-ctx uninstall --dry-run to review a full removal before it changes anything.

The context path

An agent does not always need the same representation of a project. LeanCTX provides local tools to inspect structure, public interfaces, relevant excerpts, exact lines, diffs, and full source. It also compresses eligible shell output, keeps recoverable references to source, and exposes local context state for the current task.

agent → LeanCTX context tools / shell hook → project and local tools
agent → optional local proxy                 → model provider

The proxy only records and transforms traffic it can observe. Its data must not be used to infer hidden prompts, retries, task quality, provider bills, or accepted business savings.

Use LeanCTX in your own agent

The current programmatic path is Python SDK v1 (Preview) through its declared OpenAI Agents reference-wrapper. It wraps that one declared agent lifecycle around the local Runtime; it does not choose a model, replace task logic, or turn an unobserved run into verified evidence.

pip install lean-ctx-python

from agents import Agent
from lean_ctx import LeanCTX

ctx = LeanCTX()
openai_agent = Agent(name="reviewer")
run = ctx.wrap(openai_agent).run("Review the payments module")
print(run.output)
print(run.receipt.verify())  # True only when Runtime evidence is sealed

See the Python SDK README for its declared adapter scope, compatibility, degradation behaviour, and evidence boundary.

Proof, not a percentage badge

Local observability can show context movement and compression deltas. A pu

... View full README on GitHub