Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
A super light-weight embedded code search engine CLI (AST based) that just works - improves speed and efficiency for coding agent 🌟 Star if you like it!
Cut AI token costs 95%+ on code exploration. The leading MCP server for precise, symbol-level GitHub code retrieval via tree-sitter AST. Works with Claude Code, Cursor & any MCP client. 313B+ tokens saved.
Find the ghost tokens. Fix them. Survive compaction. Avoid context quality decay.
The ripgrep of AI context: a zero-dependency C++23 CLI + MCP server for coding agents. Find what you want without reading the repo, then check you built what you meant — blast radius, tests-to-run, quality deltas. Signatures at 74.7% fewer bytes than bodies; every guess labelled, every loss published. Paddle out with a map.
High-performance code-intelligence engine for AI agents and IDE, supports 257 languages, multi repositories, based on graph, with access via CLI, MCP Server, and API. AI coding agents teammate - expose only needed information, cutting token usage up to 50x. 100% local. Discord: https://discord.gg/39MFHu3J5d
Context compression for AI coding agents: compresses tool output before it enters the model, dedups repeats to 13-token refs. Claude Code, Cursor, Codex, Kiro, Zed, any MCP client. Rust, zero LLM calls.
LLM-supervised persistent memory for AI agents — graph-based recall, cross-session knowledge, single binary. Works with DeepSeek Harness, Claude Code, OpenClaw, and any agent runtime.
Save tokens. Maximize context, Safely
Codex and Claude Code plugin (works in Claude Desktop): choose which past images go to the model with your next message. Unchecked images become placeholders, the conversation goes on, and requests stay small.
Posthorse: fresh context, same journey. No-summary context rollover for the Pi coding agent (official Pi 1.0+ or the fitchmultz/pi fork), with durable notes and history recovery.
A Claude Code mod that puts a live agent dashboard in your terminal: context and cost, advisor timeline, every permission check, subagent cards and swimlanes.
dsh-sieve: context engineering & token optimization plugin for DeepSeek Harness (DSH) — tool output filtering, context pruning, progressive skill disclosure. 36% smaller payload in offline replay. DSH 上下文管理与 token 优化节省插件。
Safety-first GUI and CLI for auditing, backing up, importing, cleaning, and trimming Codex conversations without editing internal storage.
What Claude Code is doing between your prompt and its answer, drawn live from the logs it already writes: every model call, every tool, each subagent on its own context window and its own model, and what the session produced. Local and read-only — your session content never leaves the machine.
Fast local CLI and MCP tool for compacting verbose test runners and build output.
Codex skill and CLI utility for safely configuring model context windows, effective percentages, and auto-compaction defaults.
A pure-Python system that automatically discovers, verifies, and applies relevant historical requirements for coding agents — no embeddings, no vector database, no LLM calls. Companion code for the Towards Data Science article on intent continuity.
Claude Code 状态栏:会话花费、上下文占用、5h / 7d 限额预警,区分订阅制与按量付费。单文件 Python,零依赖。· A Claude Code statusline for session cost, context usage and limit warnings.
DeepSeek Harness 插件:一键匹配模型上下文窗口,展示容量来源,支持勾选批量配置、已有窗口管理和手动编辑。
Context-pruning proxy for Claude Code and Codex: Jev judges which history is still needed, measured not claimed. POC here now, heading soon into https://github.com/compozy/compozy
A filter plugin for Open WebUI that shows detailed token, context, timing and cost statistics below each AI response: token counts (input/output/total, reasoning, cached, audio), context-window utilization, generation time, tokens/second and message/chat cost.
A tool that replaces everything that can be deterministic in repository work: search, symbols, callers, task scope, history, review and Git from one local CLI, so your AI coding agent spends its tokens on the hard part.