Compresses tool outputs, logs, files and RAG chunks locally before they reach the LLM to reduce token usage while caching originals for on-demand retrieval. Provides proxy/library/wrap modes, JSON- and code-aware compressors, and reversible compression.
Transforms unstructured documents into strongly-typed Knowledge Abstracts with one CLI command, extracting entities and relations into graphs, hypergraphs, and spatio‑temporal structures. Includes 80+ templates, multiple RAG engines, local vLLM support, Obsidian export and an MCP server.
Connects AI assistants to Figma to extract design-system variables and components, create and edit frames, sync tokens bidirectionally to DTCG/CSS, and run WCAG scans. Read-only SSE, Cloud Mode, or NPX modes expose up to 106 tools.
Installs modular Agent Skills for the Stitch MCP server to expose Stitch-powered design and coding capabilities to coding agents. Includes CLI discovery/installation, UI-to-React conversion, design-system synthesis, multi-page site generation, and Remotion video export.
Pre-indexes a project's code into a local semantic knowledge graph that Claude Code can query—fewer tool calls and faster exploration with all data kept on-device. Features FTS5 search, call/impact analysis, auto-sync watcher, and multi-language support.
A curated, security-first registry of verified, tested skills you can install into AI coding agents. Each skill is human-curated, scanned (Snyk/static analysis), and integrity-locked; delivered via a CLI and optional MCP server to multiple agents (Claude Code, Cursor, Copilot, etc.).
Fetches multi-source content (webpages, YouTube, PDFs, WeChat, paywalled articles, podcasts), uploads it to Google NotebookLM, and generates outputs such as podcasts, PPTs, mind maps, or quizzes. Differentiators: automatic paywall-bypass pipeline, Claude Code Skill integration, and CLI + MCP components for WeChat and document scraping.
Centralized operations dashboard for OpenClaw agent fleets — orchestrate boards and tasks, manage agent lifecycles, enforce approval-driven governance, and operate gateway-connected runtimes from a single UI and API.
Local integration layer that lets AI agents discover and securely call OpenAPI, MCP, GraphQL, or custom JavaScript functions. Centralizes a shared tool catalog, auth, and policy surface across multiple agents, with a local web UI and CLI for runtime control.
Provides a local MCP server that returns precise, symbol-level code (functions, classes, imports) via tree-sitter parsing so AI agents send only the bytes they need—commonly cutting code-reading token usage 95%+ and enabling compact packed responses for further savings.
Local LLM inference server for Apple Silicon that exposes an OpenAI-compatible API and a macOS menubar app. Uses continuous batching and a two-tier KV cache (RAM + SSD in safetensors) to persist context across restarts, enabling practical multi-model serving and fast local coding workflows.
Acts as an OpenAI‑compatible local and cloud gateway that routes requests across 100+ LLM providers with smart routing, load balancing, retries and fallbacks. Adds policies, rate limits, semantic caching and observability for reliable, cost‑aware inference in Docker, Electron or npm installs.