Join waitlist
Back to products
Context Gateway

Context Gateway

Make Claude Code faster and cheaper without losing context

Website github.com
Overview

What it is

Context Gateway cuts latency and token spend for Claude Code / Codex / OpenClaw by compressing tool output while preserving important context. Setup takes less than a minute. Quality-of-life features: instant context compaction and setting spend limit in Claude Code.

Intent

I need it when

Optimize token usage and reduce API costs for long-running AI agent workflows

By compressing and summarizing conversation history using configurable summarizer models, Context Gateway reduces the number of tokens sent to the LLM API on each request, lowering overall API costs while maintaining conversation context

Integrate context optimization into existing AI agent workflows without code changes

Context Gateway functions as a transparent proxy that intercepts agent-to-LLM communication, requiring only configuration of the agent type and compression trigger threshold, with no modifications to existing agent code or workflows

Prevent AI agent conversations from hitting context limits and causing delays

Context Gateway sits between AI agents (Claude Code, Cursor, etc.) and LLM APIs, automatically compressing conversation history in the background before context limits are reached, eliminating wait times when conversations get too long

Monitor and understand what happens during conversation history compaction

Context Gateway logs all compaction events to a structured JSONL file (history_compaction.jsonl), allowing users to audit and understand how their conversation history is being summarized and compressed

Drop

Not a fit when

  • User requires commercial support or SLA guarantees for production AI agent deployments
  • Organization prohibits self-hosted or locally-deployed infrastructure for security/compliance reasons
  • User needs a managed cloud service without infrastructure setup and maintenance responsibilities
  • AI agent workflow does not involve long conversation histories or context window constraints
  • User requires proprietary compression algorithms or vendor lock-in for competitive advantage
Commercials

Pricing

Free, open-source