Open-source Prompt Firewall — deflect up to 95% of redundant LLM traffic before it leaves your infrastructure. Documents: https://isartor-ai.github.io/Isartor/index.html
Free local CLI that estimates, hard-caps, and losslessly compresses the cost of AI coding agents. Delta-encodes re-read files (37.9% proven on a real OpenAI call). MIT, 100% local.
A high-performance, multi-agent observability engine designed for the Model Context Protocol (MCP). It provides a non-blocking, transparent proxy layer that implements deterministic token attribution, real-time context-window alerting, and heuristic-driven static analysis to optimize LLM metadata overhead at scale.
Builds prompt-cost discipline into Claude Code: measure every prompt, surface avoidable spend, report org-wide. Skill + UserPromptSubmit hook + MCP rollup with cited dollar/Wh/CO2e receipts.
Cost-optimized MCP server and proxy router for Claude, Cursor, and any agent. Picks the cheapest model + toolchain per use case. Drop-in, Go binary, BUSL-1.1.
A lightweight OpenClaw model router that reduces LLM costs by switching requests to cheaper models using custom rules.
llmcfo
FinOps LLM
Production-ready tiered LLM cascade router — cuts API costs by 65%
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