Ai Agents AI Agent Skills

The Web, Readable. Your AI agent spends 60,000 tokens just to look at a web page. Charlotte does it in 336. Charlotte is an MCP server that gives AI agents structured, token-efficient access to the web. Instead of dumping the full accessibility tree on every call, Charlotte returns only what the agent needs: a compact page summary on arrival, targeted queries for specific elements, and full detail

- MCP Server: code-to-tree - Using code-to-tree - Configure MCP Clients - Building (Windows) - Building (macOS) The code-to-tree server's goals are: 1. Give LLMs the capability of accurately converting source code into AST(Abstract Syntax Tree), regardless of language. 2. One standalone binary should be everything the MCP client needs. These goals imply: 1. The underlying syntax parser should be v

Build WhatsApp automations with Kapso workflows: configure WhatsApp triggers, edit workflow graphs, manage executions, deploy functions, and use databases/integrations for state. Use when automating WhatsApp conversations and event handling.

Shodh-Memory Persistent memory for AI agents. Single binary. Local-first. Runs offline. We built this because AI agents forget everything between sessions. They make the same mistakes, ask the same questions, lose context constantly. Shodh-Memory fixes that. It's a cognitive memory system—Hebbian learning, activation decay, semantic consolidation—packed into a single ~17MB binary that runs offline

The firewall for AI agents. Open-source policy enforcement for MCP. Website: policylayer.com Intercept is a deterministic enforcement proxy for the Model Context Protocol (MCP). It sits between an AI agent and an MCP server, evaluating every tools/call request against YAML-defined policies. Violating calls are blocked at the transport layer before reaching the upstream server. MCP gives AI agents

MCPServers.org | ModelScope | （更多MCP平台陆续上架中……） CRIC物业AI 是 克而瑞 专为物业行业打造的智能 AI 助理，于2025年4月25日 正式发布。 CRIC物业AI 通过行业知识库建设，结合多模态大模型 + RAG 技术，集成五大核心能力模块：行业研究、法律法规、社区治理、项目经营、文案写作，并在行业垂类知识基础上，拓展了 资讯舆情 和 人才培训 两大智能体。 克而瑞通过三个能力来构建其自身在物业AI合作领域优势： - 数据资产转化能力： 将10亿字行业语料、TB级多模态数据转化为物业行业的高质量数据集，并构建了一套行业数据质量评估体系，保障准确率和可信度； - 场景穿透能力： 聚焦20+物业行业垂直业务场景，定向选用对应领域知识库，精准匹配； - 生态进化能力： 通过每日实时监测超过500+可信资讯和数据来源，处理10万+实时数据的自更新系

The semantic engine for MCP clients. Define metrics once, query from anywhere. Docs · Getting Started · Changelog · Discord · Bonnard is an agent-native semantic layer CLI. Deploy an MCP server and governed analytics API in minutes -for AI agents, BI tools, and data teams. Define metrics and dimensions in YAML, validate locally, and ship to production. Works with Snowfl

An MCP Server to utilize Codelogic's rich software dependency data in your AI programming assistant. The server implements five tools: - codelogic-method-impact: Pulls an impact assessment from the CodeLogic server's APIs for your code. - Takes the given "method" that you're working on and its associated "class". - codelogic-database-impact: Analyzes impacts between code and database entities. - T

A local-first CLI that orchestrates multi-agent AI workflows for software development. Give it a task — or feed it your specs, PRDs, and guidelines — and it coordinates specialized agents to architect, code, review, test, and ship automatically. No cloud dependency. Bring your own API keys. Your code stays on your machine. Each stage uses a specialized AI agent with tuned prompts and parameters. T

Model Context Protocol (MCP) server for mapping clinical terminology to Observational Medical Outcomes Partnership (OMOP) concepts using Large Language Models (LLMs). The vocabulary API is supported by OMOP HUB, and you can obtain an API key from omophub.com. This server provides an agentic framework to standardize medical terms into the OMOP Common Data Model (CDM). It uses the OMOPHub API for vo

Provides score interpretation (< 0.3 good, > 0.5 skip), query optimization, and source naming for query_documents, ingest_file, ingest_data tools. Use this skill when working with RAG, searching documents, ingesting files, saving web content, or handling PDF, HTML, DOCX, TXT, Markdown.

"Code -> audit -> amend -> audit again -> pass." Blind Auditor is a mandatory code auditing system built on the MCP (Model Context Protocol). It uses a unique "Thinking Isolation" mechanism to force AI Agents to enter an independent "audit phase" and self-review their code before outputting the final result. Traditional AI coding is often "generate and output," which allows errors and biases to sl

Outlook Assistant MCP server for Outlook email, calendar, and contacts — let your AI assistant manage your inbox directly from the conversation. Outlook Assistant connects AI assistants to your Microsoft Outlook account through the Model Context Protocol. Ask your AI assistant to search your inbox, send emails, schedule meetings, manage contacts, and configure mailbox settings — without leaving th

Use this skill when an AI agent needs to join Wiplash.ai, search the Waterpark-ranked feed, publish posts including externally hosted apps, leave feedback, vote, use private Cabanas, or inspect agent profiles through the Wiplash Agent Network API.

&nbsp;&nbsp; Give AI assistants (Claude, Cursor, VS Code, etc.) the ability to control your desktop and automate tasks across any application. Claude Code (one-liner): Other clients (Cursor, VS Code, Windsurf, etc.): Add to your MCP config file: See the MCP Agent README for detailed setup instructions. - Uses your browser session - no need to relogin, keeps all your cookies and auth - Doesn't take

Debug AI traces, find exceptions, analyze sessions, and manage prompts via Langfuse MCP. Also handles MCP setup and configuration.

Model Context Protocol server for TorrentClaw — giving AI assistants the ability to search movies and TV shows, find torrents with magnet links, check streaming availability, and explore cast/crew metadata. torrentclaw-mcp is developed by TorrentClaw as part of its open-source ecosystem. It wraps the TorrentClaw API into the MCP standard so that any compatible AI assistant (Claude, GPT, etc.) can

Decompose any text into classified semantic units — authority, risk, attention, entities. No LLM. Deterministic.

OMOPHub MCP Server Medical vocabularies for AI agents. Search, map, and navigate 10M+ OMOP concepts: SNOMED CT, ICD-10, RxNorm, LOINC, and more. Directly from Claude, Cursor, VS Code, or any MCP-compatible client. Quick Start · Examples · Working with medical vocabularies today means downloading multi-gigabyte CSV files, loading them into a local database, and writing SQL to find what you need. Ev

A Model Context Protocol (MCP) server that provides local vector database functionality using FAISS for Retrieval-Augmented Generation (RAG) applications. - Local Vector Storage: Uses FAISS for efficient similarity search without external dependencies - Document Ingestion: Automatically chunks and embeds documents for storage - Semantic Search: Query documents using natural language with sentence

Find emails needing follow-up -- unanswered sent emails, flagged unreplied, draft contextual responses

Your MCPs, supercharged. Find any tool instantly, execute with code mode, run on schedule, discover skills, load Photons, ready for any client. Smart loading saves tokens and energy. Instead of your AI juggling 50+ tools scattered across different MCPs, NCP gives it a single, unified interface with code mode execution, scheduling, skills discovery, and custom Photons. Your AI sees just 2-3 simple

An AI coding assistant built in Rust that provides both command-line and graphical interfaces for autonomous code analysis and modification. Multi-Modal Tool Execution: Adapts to different LLM capabilities with pluggable tool invocation modes - native function calling, XML-style tags, and triple-caret blocks - ensuring compatibility across various AI providers. Real-Time Streaming Interface: Advan

A multi-model AI orchestration MCP server for automated code review and LLM-powered analysis. Multi-MCP integrates with Claude Code CLI to orchestrate multiple AI models (OpenAI GPT, Anthropic Claude, Google Gemini) for code quality checks, security analysis (OWASP Top 10), and multi-agent consensus. Built on the Model Context Protocol (MCP), this tool enables Python developers and DevOps teams to