


Compression V2 cuts coding-agent token bills with three techniques across two layers: sharper tool result trimming, new task-aware tool surface reduction, and output brevity. Drop-in for Claude Code, Codex, OpenCode, and Cursor. Semantically lossless.
Edgee Claude Code Compressor V2 is a token compression tool designed specifically for coding agents. It reduces the number of tokens sent to large language models during coding sessions by applying three distinct compression techniques across two layers. The result is a β50% reduction in tokens on a typical session β dropping from 18,420 to 9,210 tokens β while remaining semantically lossless on code-oriented tasks. It works as a drop-in CLI wrapper with zero code changes and integrates with existing API keys and plans.
This improved technique filters CLI and tool results before they reach the model. It removes boilerplate, pagination markers, ANSI escape sequences, repeated headers, and verbose framing. A 980-token directory listing becomes a dense 340-token one that the model reads just as well, saving β10% of tokens in a typical session.
New in V2, this technique runs a small, fast classifier that scores each tool against the classified task. It then strips or down-scopes irrelevant tools before the request hits the model. Your IDE still exposes everything, but the model only sees a curated, task-relevant subset β no more manual toggling of MCP servers.
This new technique reduces the verbosity of model responses without losing technical content. You pick the level (light, medium, hard) to trade aggressiveness against tone. Though output is only ~1% of token volume, it's the traffic you pay the most for, making this β30% reduction highly valuable.
Compression V2 cuts token bills by half while keeping every bit of context the model needs β semantically lossless on code tasks.
This isn't just about trimming tokens. The three techniques work together across both input and output layers, each independently toggleable via config flags. The tool surface reduction is particularly clever β it eliminates the need to manually manage which MCP servers are active, letting the classifier handle relevance automatically. With <12ms P50 gateway overhead and zero code changes, the performance impact is negligible while the cost savings are substantial.
You use coding agents like Claude Code, Codex, OpenCode, or Cursor and want to reduce token costs without changing your workflow. It's especially valuable if you run frequent sessions where even small per-request savings add up quickly, or if you're tired of manually toggling MCP servers on and off. The drop-in CLI wrapper means you can start saving tokens in minutes with no code changes.
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