LLM & AI Agent Skills

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:

Persistent memory for Claude Code. Also: loop detection, scope guards, code analysis, and a local LLM for second opinions. Claude Code forgets everything between sessions and after context compaction. Mini Claude provides: - Checkpoints - Save task state, auto-restore after compaction - Mistake memory - Log errors, get warned next time you touch that file - Decision memory - Log WHY you chose some

Overview • Quick Start • Supported Data Providers • FinData is an open-source Model Context Protocol(MCP) Server that provides professional financial data access capabilities for LLM. It supports various data providers such as Tushare, Wind, DataYes, etc. This enables AI applications to quickly retrieve financial data. Fully supports both Stdio and SSE transports, offering flexibility for differen

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

Markmap MCP Server is based on the Model Context Protocol (MCP) that allows one-click conversion of Markdown text to interactive mind maps, built on the open source project markmap. The generated mind maps support rich interactive operations and can be exported in various image formats. - 🌠 Markdown to Mind Map: Convert Markdown text to interactive mind maps - 🖼️ Multi-format Export: Support for

The memory system for AI coding agents. Decisions, lessons, and context that persist across sessions. mcp-name: io.github.omega-memory/omega-memory AI coding agents are stateless. Every new session starts from zero. - Context loss. Agents forget every decision, preference, and architectural choice between sessions. Developers spend 10-30 minutes per session re-explaining context that was already e

An MCP (Model Context Protocol) server that connects your Mendeley reference library to LLM applications like Claude Desktop, Cursor, and other MCP-compatible clients. - Search your library - Find papers by title, author, abstract, or notes - Browse folders - Navigate your collection structure - Get full metadata - Retrieve complete document details including abstracts - Search global catalog - Ac

MCP server that fetches YouTube video transcripts and optionally summarizes them. - Fetch transcripts in multiple formats (text, JSON, SRT, WebVTT, pretty-print) - Summarize videos — returns transcript with instructions for the LLM to produce a summary - List available languages for any video's transcripts - Flexible URL parsing — accepts full YouTube URLs (youtube.com/watch?v=, youtu.be/, youtube

AI-powered developer workflows with cost optimization and pattern learning. Run code review, debugging, testing, and release workflows from your terminal or Claude Code. Smart tier routing saves 34-86% on LLM costs. -brightgreen) Empathy Framework is evolving to focus exclusively on Anthropic/Claude to unlock features impossible with multi-provider abstraction: - 📦 Prompt Caching: 90% cost reduct

A Model Context Protocol (MCP) server that provides agentic tools for interacting with the Trieve API. This server enables AI agents to search and interact with Trieve datasets through a standardized interface. - Search across Trieve datasets using semantic search - List and access dataset information - Support for both environment variables and command-line arguments - Built with TypeScript for t

ScrapeBadger MCP Server Give your AI agents access to Twitter/X data via the Model Context Protocol ScrapeBadger MCP Server is a Model Context Protocol (MCP) server that enables AI assistants like Claude, ChatGPT, Cursor, Windsurf, and other MCP-compatible clients to access Twitter/X data through the ScrapeBadger API. With this MCP server, your AI can: - Get Twitter user profiles, followers, and f

Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa

The Parallel Task MCP allows initiating deep research or task groups directly from your favorite LLM client. It can be a great way to get to know Parallel’s different APIs by exploring their capabilities, but can also be used as a way to easily do small experiments while developing production systems using Parallel APIs. Please read our MCP docs here for more details. The official installation ins

The Web MCP 🌐 Give your AI real-time web superpowers Seamlessly connect LLMs to the live web without getting blocked Quick Start • Features • 🎉 Free Tier Available! 🎉 5,000 requests/month FREE Perfect for prototyping and everyday AI workflows 🚀 Launch Week - January 2026 🚀 5 Days of Major Releases! 📦 Tool Groups 🧙 Setup Wizard ⚡ Token Efficiency 🏢 Enterprise Integrations 📊 Observability

Advanced search and retrieval for web crawler data. With mcp-server-webcrawl, your AI client filters and analyzes web content under your direction or autonomously. The server includes a fulltext search interface with boolean support, and resource filtering by type, HTTP status, and more. mcp-server-webcrawl provides the LLM a complete menu with which to search, and works with a variety of web craw

Transcribe MCP Automate your transcriptions with AI. Transcribe MCP instantly connects your account to assistants like Claude, Windsurf, Cursor, and more so they can automate tasks on your behalf. The Local Server can add local files for transcription and return result to your Assistant in seconds. - ⚡ Fast, lightweight and LLM-friendly. No special ASR models needed, no setup and fighting python p

MCP server for the Urlbox Screenshot API. Enables your client to take screenshots, generate PDFs, extract HTML/markdown, and more from websites. Visit Urlbox for more information, and have a read of our docs or chat with your LLM post install to get a good understanding of its options and capabilities. 1. Install dependencies and build: 2. Get Urlbox API credentials: - Sign up at urlbox.com - Get

CSL-Core (Chimera Specification Language) is a deterministic safety layer for AI agents. Write rules in .csl files, verify them mathematically with Z3, enforce them at runtime — outside the model. The LLM never sees the rules. It simply cannot violate them. Originally built for Project Chimera, now open-source for any AI system. This doesn't work. LLMs can be prompt-injected, rules are probabilist

A Model Context Protocol (MCP) server that provides access to the full Massive.com financial data API through an LLM-friendly interface. Rather than exposing one tool per endpoint, this server gives the LLM four composable tools — search, docs, call, and query — that cover the entire Massive.com API surface. Data can be stored in-memory as DataFrames, queried with SQL, and enriched with built-in f

A Model Context Protocol server that enables LLMs to interact with GraphQL APIs. This implementation provides schema introspection and query execution capabilities, allowing models to discover and use GraphQL APIs dynamically. Run mcp-graphql with the correct endpoint, it will automatically try to introspect your queries. - graphql-schema: The server exposes the GraphQL schema as a resource that c

Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu

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

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

A Model Context Protocol (MCP) server for accessing the Climatiq API to calculate carbon emissions. This allows AI assistants to perform real-time carbon calculations and provide climate impact insights. This MCP server integrates with the Climatiq API to provide carbon emission calculations for AI assistants: - set-api-key: Configure the Climatiq API key used for authentication - electricity-emis