Context Optimization
Top open-source Context Optimization AI systems, agents, and MCP tools.
Discover and install verified Context Optimization AI systems, autonomous agent skills, and Model Context Protocol servers on AIStoreHub. Reusable, security-scanned, and ready for 1-click execution in Cursor, Claude Code, and terminal workflows.
Available AI Systems & Skills (26)
Open in Advanced FilterThe open source runtime that turns your APIs AI-Native, without rebuilding them
Cut AI context cost without trusting the compressor. Every reduction is reversible, byte-exact recoverable, and carries an auditable receipt. Local-first, works through proxy, MCP, SDK, or agent wrapper.
23 Claude Code plugins: TDD enforcement hooks, git/PR workflows, spec-driven development, code review, project lifecycle, fix-from-error, maintenance automation, context optimization, research, and multi-LLM delegation. 186 skills, 128 commands, 54 agents.
100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source.
Context window optimization for AI coding agents. Sandboxes tool output (98% reduction), persists session memory, and enforces routing across 17 platforms via MCP + hooks.
Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More
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!
MCP server for AI image generation and editing with automatic prompt optimization and quality presets. Supports Nano Banana (Gemini), OpenAI GPT Image, and BytePlus Seedream.
Local streaming reverse proxy between AI coding agents (Claude Code, Cursor, Codex) and model APIs (Anthropic, OpenAI, Gemini, MiniMax). Meters every token + USD cost, compacts bloated context to cut pay-per-token API spend, and runs shadow-eval to prove quality held. ccusage-style metering + live local dashboard.
MCP server for free Google AI Mode search with citations. Query optimization, CAPTCHA handling, multi-agent support. Works with Claude Code, Cursor, Cline, Windsurf.
One command gives AI agents instant codebase context. ~250 tokens replaces 50,000+ tokens of exploration. Auto-configures Claude Code, Cursor, Aider.
Stop Claude Code from burning through your quota in 20 minutes. Auto-rotates oversized sessions and preserves context.
Three hooks that fix Claude Code's attention drift. Cited research, one-line install.
One zero-dependency CLI for every MCP server and agent skill. Token optimization, tool discovery and context compression: 71,929 -> 581 tokens (-99.2%, measured), schemas stay out of context. One config for Claude Code, Codex, Cursor, every agent. 341KB, pure Python. | 零依赖 CLI：管所有 MCP 工具与技能，工具发现省 99.2% token。
Working memory for Claude Code - persistent context and multi-instance coordination
Your agent pays twice for output it has already seen. OMNI returns a handle instead: 97.2% off a file read twice. Nothing deleted, nothing invented.
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.
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。
Fast Rust launcher for DeepSeek Harness, with clear Claude Code/Codex migration, model setup and lightweight local tools
A branch-aware Codex skill that saves compact project context, relevant skills, blockers, and next actions so you can start a fresh chat and continue work seamlessly—without carrying unnecessary history or wasting tokens.
CLI proxy that reduces LLM token usage by 60-90%. Declarative YAML filters for Claude Code, Cursor, Copilot, Gemini. rtk alternative in Go.
Turn Claude Code into its own Meta-Harness — a skill that evolves the scaffolding around a fixed model (memory, retrieval, context, prompts) via a native propose→score→Pareto loop. Native reimplementation of Meta-Harness (Lee et al. 2026).
Delta MCP is a free app that sits between your AI apps and their MCP servers: any server, every tool. It checks each task before it runs, applies it all or nothing, reads back what it changed and lets you undo it. Far fewer tokens on multi-step tasks, and shortcuts that run on a schedule. Coming soon for macOS, Windows and Linux.
Make your OpenClaw AI agent faster, smarter, and cheaper. Speed optimization, memory architecture, context management, model selection, and one-shot development guide.
Build & Monetize for Context Optimization
Have you created an autonomous agent, MCP server, or Claude Code skill for Context Optimization? Publish it to AIStoreHub with dual-currency checkout (USD $ + INR ₹) and earn 85–90% net revenue.