Structured skill framework for Claude Code. 130 skills, persistent memory, TokenStack compression, localhost dashboard with 3-agent runner, real-time streaming, MCP tools.

(HAM) Memory system for AI coding agents. Cut token usage by 80% by scoping context to directories.

Like htop, but for AI coding agents. Monitor Claude Code & Codex CLI sessions, tokens, context window, rate limits, and ports in real-time.

A headless browser for AI agents that fetches modern web pages, runs JavaScript, manages sessions, and returns token-efficient Markdown.

Token conscious database MCP server for Postgres, MySQL, SQL Server, MariaDB, SQLite.

pctx is the execution layer for agentic tool calls. It auto-converts agent tools and MCP servers into code that runs in secure sandboxes for token-efficient workflows.

Turn any website into a compact CLI tailored for AI agents. Browse the web in hundreds of tokens, not tens of thousands.

30 sec to give your AI agents persistent memory. Reduce 90% token consumption while also maintaining quality.

Agent-skills marketplace for Claude Code, Codex and Cursor: RPA BDD workflow, Logika (Chelpanov formal logic), token-cost, MikroTik config generator

A lightweight Linear MCP server for Claude Code that exposes one tool with action dispatch (search, get, update, comment, create, graphql, help) using ~500 tokens instead of the standard MCP's ~17,000.

🌼 A token-friendly local MCP server for DaisyUI component documentation using their public llms.txt.

🧠 The right skill, one API call. AI agent skills registry with token-efficient skill resolution. 5,000+ skills from 500+ top repos.

Rebuild the object in a reference image as a code-only, procedural, quality-gated, animation-ready Three.js model. Token-efficient image-to-3D.

MCP server providing token-efficient access to OpenAPI/Swagger specs via MCP Resource Templates for client-side exploration.

Agentic-MCP, Progressive MCP client with three-layer lazy loading. Validates AgentSkills.io pattern for efficient token usage. Use MCP without pre-install & wasting full-loading

Instant, accurate Unreal Engine API lookups instead of expensive source file reads, saving your agent tokens, context, and hallucinations.

Save 40%+ on agent token costs with code graphs: call graphs, dependency graphs, dead code detection, and blast radius analysis.

Context engine for large codebases, exposed through MCP. Gives AI coding agents precise repository context; benchmarked at frontier-agent quality with ~25x lower model cost and 45% fewer tokens with semantic search.

Graph-based long-term memory skill for AI (LLM) coding agents — faster context, fewer tokens, safer refactors

A browser runtime that lets AI agents control your real Chrome browser via MCP. Agents can explore websites, generate operation manuals, and reuse them to save tokens. AI操控你的真实浏览器。

Natural Context Provider (NCP). Your MCPs, supercharged. Find any tool instantly, load on demand, run on schedule, ready for any client. Smart loading saves tokens and energy.

A reusable Agent Skill for designing, reviewing, and implementing UI/UX with Google Material Design 3, Material You, M3 Expressive, accessibility, adaptive layouts, and semantic design tokens.

AI Badger - Local-first tool that extracts focused repo context for any AI chat (Claude, ChatGPT, Grok, etc.) without wasting tokens on irrelevant files.

Config-driven CLI tool that compresses command output before it reaches an LLM context