LLM & AI Agent Skills

A Model Context Protocol (MCP) server implementation for DuckDB, providing database interaction capabilities through MCP tools. It would be interesting to have LLM analyze it. DuckDB is suitable for local analysis. This server enables interaction with a DuckDB database through the Model Context Protocol, allowing for database operations like querying, table creation, and schema inspection. Current

📖 Blog Post: Learn more about this project in the detailed blog post: Telephony MCP Server for Agentic AI and Language Models This directory contains MCP (Model Context Protocol) Server tools for telephony operations, such as making voice calls and sending SMS messages using the Vonage API. These tools are designed to be integrated with Large Language Model (LLM) applications, enabling LLMs to pe

deco Studio Open-source · TypeScript-first · Deploy anywhere Open-source private AI workspace for organizations. decocms.com/studio Studio packages the infrastructure behind an internal AI rollout: model routing, MCP authentication, agent configuration, SSO, RBAC, audit logs, and usage accounting. Your teams get chat. You keep control. Under the hood it's one control plane for your AI agents — one

⚡ Fully automated MCP server built on top of apktool to analyze Android APKs using LLMs like Claude — uncover vulnerabilities, parse manifests, and reverse engineer effortlessly. Image generated using AI tools. apktool-mcp-server is a MCP server for the Apk Tool that integrates directly with Model Context Protocol (MCP) to provide live reverse engineering support with LLMs like Claude. Think: "Dec

This repository is an example of how to create a MCP server for Qdrant, a vector search engine. An official Model Context Protocol server for keeping and retrieving memories in the Qdrant vector search engine. It acts as a semantic memory layer on top of the Qdrant database. 1. qdrant-store - Store some information in the Qdrant database - information (string): Information to store - metadata (JSO

An MCP server implementation that integrates the SearXNG API, providing web search capabilities. - Web Search: General queries, news, articles, with pagination. - URL Content Reading: Advanced content extraction with pagination, section filtering, and heading extraction. - Intelligent Caching: URL content is cached with TTL (Time-To-Live) to improve performance and reduce redundant requests. - Pag

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

Own your AI. Agents, memory, tools, and identity that live on your Mac. Built purely in Swift. Fully offline. Open source. Download for Mac · Plugin Registry Models are getting cheaper and more interchangeable by the day. What's irreplaceable is the layer around them -- your context, your memory, your tools, your identity. Others keep that layer on their servers. Osaurus keeps it on your machine.

The server uses the MCP protocol to share access to a local Home Assistant instance with an LLM application. A powerful bridge between your Home Assistant instance and Language Learning Models (LLMs), enabling natural language control and monitoring of your smart home devices through the Model Context Protocol (MCP). This server provides a comprehensive API for managing your entire Home Assistant

This model context protocol (MCP) server interfaces with the CyberChef Server API. Allowing you to use any LLM/MCP client of your choosing to utilise the tools and resources within CyberChef. 🧰 Available Tools and Resources - getcyberchefoperationscategories: resource - gets updated Cyber Chef categories for additional context / selection of the correct operations - getcyberchefoperationbycategor

A Mattermost integration that connects to Model Context Protocol (MCP) servers, leveraging a LangGraph-based AI agent to provide an intelligent interface for interacting with users and executing tools directly within Mattermost. - 🤖 Langgraph Agent Integration: Uses a LangGraph agent to understand user requests and orchestrate responses. - 🔌 MCP Server Integration: Connects to multiple MCP serve

Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.

A powerful Ghidra extension that provides an MCP (Model Context Protocol) server, enabling AI assistants and other tools to interact with Ghidra's reverse engineering capabilities through a standardized API. GhidrAssistMCP bridges the gap between AI-powered analysis tools and Ghidra's comprehensive reverse engineering platform. By implementing the Model Context Protocol, this extension allows exte

A Model Context Protocol (MCP) server that automates optimization and analysis using Optuna. The Optuna MCP Server can be used in the following use cases, for example. - Automated hyperparameter optimization by LLMs - Interactive analysis of Optuna's optimization results via chat interface - Optimize input and output of other MCP tools For details, see the Examples section. The Optuna MCP server c

A Model Context Protocol (MCP) server that integrates with Tilt to provide programmatic access to Tilt resources and logs through LLM applications. Imagine prompting like this: The key insight is you no longer need to tell your LLM how to build and deploy your code. Instead, you can simply ask it to what to build and deploy. Tilt is a powerful tool for working with Docker/Kubernetes workloads. Wit

Hardware-accelerated persistent memory for AI agents. Local-first. No cloud. One-time payment. 66.9% on LoCoMo benchmark (adjusted). Under 1ms retrieval. Zero cloud dependency. Retrieval pipeline rebuilt from scratch. - bge-small-en-v1.5 bi-encoder + ms-marco cross-encoder reranker (spec-decode architecture) - BM25 + Porter-stemmed BM25 + named entity injection, fused via RRF - MAGMA graph layer —

A Model Context Protocol (MCP) server that enables Claude Desktop (and other MCP clients) to generate images, videos, music, and audio using Fal.ai models. - Native Async API - Uses falclient.runasync() for optimal performance - Queue Support - Long-running tasks (video/music) use queue API with progress updates - Non-blocking - All operations are truly asynchronous - STDIO - Traditional Model Con

This project provides Model Context Protocol (MCP) for the Mifos X Ecosystem, enabling AI agents to access financial data and operations. Implementations is available in Java (Quarkus). Use the MCP Inspector to test and debug your server: This starts a local web UI to connect to your MCP server via STDIO or SSE. Prerequisites: JDK 21+, Maven 1. Configure environment variables in your shell or IDE:

通过 uvx 安装并运行： 安装完成后，直接运行： 运行后你可以直接使用工具，例如： 或（如果是 uvx 安装）： 好的，这是转换后的 Markdown 版本： 好的，这是转换后的 Markdown 版本： 1. 配置环境变量（可选） 你可以通过 .env 文件或系统环境变量配置 DolphinDB 的连接信息： 也可以不设置，系统将使用默认值。 该命令会启动 MCP 插件服务，供外部调用。 3. FastMCP Agent 使用示例 启动后，你的工具将通过 FastMCP 对外暴露以下函数接口： listtbs(dbName: str) querytablediskusage(database: str, tableName: str) querydolphindb(script: str) 可通过 MCP 前端界面或对接 LLM 工具链来进行访问。

An MCP (Model Context Protocol) server that provides unified access to multiple Large Language Model APIs for AI coding environments like Cursor and Claude Desktop. - 🌐 8 LLM Providers – ChatGPT, Claude, DeepSeek, Gemini, Grok, Kimi, Perplexity, Mistral - 🎯 Smart Model Selection – Tag-based preferences (coding, business, reasoning, math, creative, general) - 📊 Prompt Logging – Track all prompts

CRUD operations for knowledge base docs — add, delete, update metadata, embed. Requires GNOSIS_MCP_WRITABLE=true.

An MCP server that delivers crypto ETF flow data to power AI agents' decision-making. - Unified Tool: The getetfflow tool dynamically fetches historical ETF flow data for BTC or ETH. - Markdown Table Output: Leverages pivot tables to present data with ETF tickers as columns, dates as rows, and a total column for summed flows. - Prompt Guidance: Includes a prompt (etfflowprompt) to streamline LLM i

Author: Syncfusion Homepage: https://boldsign.com An MCP server designed to facilitate interaction between Large Language Models (LLMs) and the BoldSign API. The Model Context Protocol (MCP) extends LLM capabilities, enabling them to act as agents when connecting with external systems. This project contains various tools that interact with the BoldSign API to manage templates and documents for you

- 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