Compresr AI's Context Gateway addresses the performance bottleneck of long AI agent conversations by providing instant history compaction and context optimization. It targets users of AI-powered development tools and agents, enabling seamless, uninterrupted workflows by eliminating delays caused by context window limits.

How It Works

This project functions as an agentic proxy, intercepting communication between an AI agent and its underlying LLM API. Its core innovation lies in performing conversation history summarization and compaction asynchronously in the background. This pre-computation ensures that when the context window limit is approached, the optimized context is immediately available, preventing user-facing delays and maintaining agent responsiveness.

Quick Start & Requirements

Installation is straightforward via a shell script: curl -fsSL https://compresr.ai/install | sh. A guided, interactive TUI wizard assists users in selecting supported agents (e.g., claude_code, cursor, openclaw, or custom configurations), setting up summarizer models and API keys, enabling optional Slack notifications, and defining the compression trigger threshold (defaulting to 75% context usage).

Highlighted Details

• Provides instantaneous context optimization for AI agent workflows, preventing user wait times.
• Leverages background, pre-computed summarization to maintain agent performance.
• Offers direct integrations with popular IDEs like Claude Code and Cursor.
• Supports custom agent configurations for broader applicability.

Maintenance & Community

The project is backed by Y Combinator (YC) and actively encourages community contributions, directing interested parties to their Discord server for engagement.

Licensing & Compatibility

The specific open-source license is not detailed in the provided README. Compatibility for commercial use or integration into closed-source projects would require clarification on licensing terms.

Limitations & Caveats

The current focus is on specific IDE integrations, with custom agent support requiring user configuration. The README does not detail potential resource overheads associated with background compaction processes.