Cursor Install Guide
AI code editor frequently used with developer-focused MCP servers.
MCP Servers
⚠️ This implementation stores OAuth credentials in ./mnt/mcp-creds/ which are currently committed to the repository. Proper OAuth flow for MCP servers is coming soon to the Agencii platform.
Evidence-grounded repository audit CLI - deterministic scanner, MCP server, live dashboard, and a GitHub Action that posts PR diffs.
Total recall for your terminal. Shared memory for your AI agents.
built by an autonomous agent · sibyl labs llc
An MCP server that queries public SearXNG instances, parsing HTML contents into a JSON result
Spring AI Playground is a cross-platform desktop app for building, testing, validating, and executing MCP tools in a controlled local environment.
A domain harness for AI-assisted mobile development and testing. Unified device logs, network traffic interception, and UI automation — exposed through APIs and MCP tools that let AI agents...
An MCP server that lets AI agents read and draw on the Figma canvas — safely. Paired with a Figma plugin, it provides structured verification, safe-by-default drawing, and resilient multi-window...
Your AI assistant now remembers everything. Forever. Across every conversation.
Stop rewriting your tools. Just adapt them.
Use any MCP server or HTTP API as a standard CLI command. A lightweight daemon + CLI that turns remote MCP tools and configured HTTP endpoints into native shell commands your agent or script can call...
Streamable HTTP MCP server for Claude.ai custom connectors.
Agent Skills
Agent Harness · Spring Boot inside · One JAR to ship
Pure python3 implementation for working with iDevices (iPhone, etc...).
从多项目日常使用中提炼的 Claude Code 工作流模板——涵盖记忆管理、上下文工程与任务路由。
An open-source biomedical AI research assistant built on OpenClaw and Claude Code, integrating 140 K-Dense Scientific Skills for bioinformatics, drug discovery, clinical research, and more.
dotagents One canonical .agents folder that powers all your AI tools.
This repository contains hands-on tutorials for learning LangChain, LangGraph, and Deep Agents, organized into two learning tracks:
A self-improving product system that reads daily reports, identifies the #1 actionable priority, and autonomously implements it.
Modern agents are not "a prompt + a tool." They are — with identity, memory, skills, tools, MCP integrations, guardrails, observability, evals, and a provider strategy.
Analysis, Comparison, Trends, Rankings of Open Source Software, you can also get insight from more than 10 billion with natural language (powered by LLM). Follow us on Twitter: https://twitter.
Platform design skill pack: 450+ rules for Apple HIG, Material Design 3, and WCAG 2.2 across iOS, iPadOS, macOS, watchOS, visionOS, tvOS, Android, and Web.
The practical guide to building AI agent harnesses — with real code examples you can copy and run.
本书围绕 DeerFlow 2.0，从理论到源码，系统讲解如何进行二次开发。 所有代码示例均基于真实源码，确保与 DeerFlow 实现保持一致。