AI Token Processing

CLI proxy that auto-compresses shell command output, reducing LLM token consumption by 60-90%, single Rust binary with zero dependencies.

CONNECT tunnel proxy with 50-90% token savings via system prompt caching, file diffing, history compression, and deduplication.

Zero-config local proxy and command engine with 30-95% token savings, slash commands, and 20+ provider model auto-routing.

Meta-installer bundling Headroom context compression, RTK CLI compression, and Memory system in one command.

Semantic compression proxy with 350+ rules and local LLM (Qwen 2.5) semantic condensation, 1,408 req/s concurrency.

Token compression proxy with 9-level dial (15-72%), Caveman output mode, zero code changes required.

Context optimization layer with 47-92% compression, cross-agent shared memory, and reversible compression (CCR), Python/TS dual language.

Mathematical prompt compression using semantic chunking, mutual-information pruning, and Lost-in-the-Middle reordering, CPU-only no GPU needed.

Python context compression middleware with 60-80% savings, quality threshold auto-fallback, and 5 integration surfaces.

MCP-specific stdio proxy that offloads large tool outputs to artifact store and returns compact previews, ~98% savings.

Self-hosted token cost analytics platform, Postgres-native, tracks 74+ models with per-user per-endpoint per-day cost attribution.

Project token cost forecaster, describe your project in natural language and get per-task token estimates with optimal model recommendations.