Context Gateway

Product Introduction

1. Definition: Context Gateway is an agentic proxy middleware designed for AI development workflows. It operates as a real-time compression layer between AI agents (like Claude Code, Cursor IDE, or OpenClaw) and LLM APIs.
2. Core Value Proposition: It eliminates latency and reduces token consumption by dynamically compressing tool outputs while preserving critical context, enabling uninterrupted AI agent operations and cost-efficient LLM usage.

Main Features

1. Instant Context Compaction:
   • How it works: Uses background summarization models to pre-compress conversation history when context limits approach. Compression triggers at user-defined thresholds (default: 75% context window saturation).
   • Technology: Integrates with Claude API, Codex, and OpenClaw via configurable summarizer models. Logs compaction events in history_compaction.jsonl.
2. Multi-Agent Support:
   • How it works: Native integration with Claude Code, Cursor IDE, and OpenClaw via interactive TUI wizard. Supports custom agent configurations through YAML-based setups.
   • Technology: Go-based CLI with pre-configured agent templates. Auto-detects agent-specific API endpoints for seamless proxying.
3. Token Spend Controls:
   • How it works: Enforces usage caps for Claude Code via API call monitoring. Alerts users via Slack notifications when approaching limits.
   • Technology: Real-time token counting with sliding-window accounting. Integrates with Slack webhooks for spend-limit warnings.

Problems Solved

1. Pain Point: Eliminates context window overflow delays in AI coding assistants. Prevents workflow interruption when conversations exceed LLM token limits.
2. Target Audience:
   • AI Engineers optimizing Claude/Codex token efficiency
   • React/Python developers using Cursor IDE
   • DevOps teams managing OpenClaw deployments
3. Use Cases:
   • Maintaining IDE responsiveness during long debugging sessions
   • Reducing Claude API costs for code-generation heavy projects
   • Preventing context truncation in automated testing pipelines

Unique Advantages

1. Differentiation: Unlike manual context trimming, it preserves semantic relationships during compression. Outperforms basic caching proxies by retaining domain-specific context (e.g., variable references in code).
2. Key Innovation: Preemptive background compaction using sliding-window token analysis. This patent-pending approach compresses non-active conversation segments before users hit context limits.

Frequently Asked Questions (FAQ)

1. How does Context Gateway reduce Claude token costs?
   It compresses tool outputs and conversation history by 30-60% using lossy context preservation algorithms, directly lowering per-request token consumption.
2. Can Context Gateway work with custom AI agents?
   Yes, the TUI wizard supports custom endpoint configuration for any API-compatible agent, including private LLM deployments.
3. What summarization models does Context Gateway support?
   Configurable integration with Claude Haiku, GPT-3.5-Turbo, and Llama 2 via API keys. Custom summarizers can be added via Go plugin system.
4. How does instant compaction impact AI response quality?
   Compression prioritizes code syntax patterns and error traces using domain-specific heuristics, maintaining >92% functional equivalence in benchmark tests.
5. Is there latency overhead for context compression?
   Background processing adds <50ms p99 latency. Net latency reduction occurs by avoiding full context-window recomputations.