A non-minimal Neovim config built to work most efficiently with Frontend Development

An MCP server for accessing NWB (Neurodata Without Borders) files, providing AI agents with easy access to neuroscience data.

Provide seamless access to Old School RuneScape Wiki content and game data files through powerful search and retrieval tools. Enable efficient exploration of game variables, interface definitions, NPCs, items, animations, and more to enhance your OSRS-related projects. Integrate comprehensive OSRS knowledge directly into your applications with ease.

AI-powered medical document management for cancer patients. Google Drive, Gmail, Calendar via MCP.

Local stdio MCP server for contracts workspace operations

The FileSearch MCP Server is a lightweight FastMCP service that takes a user question, calls OpenAI’s File Search on a designated vector store, and returns the raw ranked chunks unchanged.

Splits and extracts portions of OpenAPI specification files into smaller, more focused files while preserving referenced components for improved documentation and maintainability.

Search and retrieve agent instruction files including system prompts, skills, and workflows.

**AI code quality gate** that catches what traditional linters can't — hallucinated packages, phantom dependencies, stale APIs, context breaks, and security anti-patterns in AI-generated code. ✅ **5 languages**: TypeScript, JavaScript, Python, Java, Go, Kotlin ✅ **3 SLA levels**: L1 (fast structural), L2 (local AI), L3 (deep remote AI) ✅ **CI/CD integration**: GitHub Action + GitLab Component + CLI ✅ **MCP tools**: scan_directory, scan_diff, explain_issue, heal_code Free, open-source, no API key required.

Twitter/X Data · User Profiles · Tweet Search · Follower Events · KOL Tracking

Ask the oracle when you're stuck. Invoke GPT-5 Pro with a custom context and files.

OCI File Storage MCP server

OCI Object Storage Service MCP server

MCP Server for use with msgraph calls to mail, calendar, and files

MCP server for Primavera P6 XER schedule files — parse, analyze, and quality-check with AI

Real Chrome profiles with site intelligence — already logged in, PII anonymization, sessions persist

Leverages pandas, numpy, and matplotlib to enable powerful data manipulation, statistical analysis, and visualization for data-driven projects.

MCP server to give llms such as Claude, GitHub Copilot etc full PowerBI model context (from input .pbix) through tools based on PBIXRay python package.

Provides comprehensive PDF processing capabilities through PyMuPDF, including text operations, page manipulation, image handling, form field management, annotation support, and metadata editing with intelligent auto-cropping and timestamped output files for document automation workflows.

MCP server for PDFPipe - let AI assistants convert any PDF URL to structured data. Handles inline PDFs, auto-download attachments, redirects, and token-gated files

Convert PDF documents into editable DOCX files seamlessly. Enable your applications to extract and transform PDF content into Word format efficiently. Simplify document workflows by integrating this conversion capability.

PentestThinkingMCP: AI-Driven Multi-Stage Penetration Testing Framework Part of the LIMA Research Project – Accepted at IEEE FMLDS 2025 Developed by Mohammad Ibrahim Saleem, Cybersecurity Researcher, University of Houston PentestThinkingMCP is an AI-powered MCP (Model Context Protocol) server developed as part of the LIMA research project. This work was recently accepted as a full paper at IEEE FMLDS 2025. The server automates and optimizes penetration testing workflows by planning complex, multi-stage attack paths using advanced reasoning methods such as Beam Search and Monte Carlo Tree Search (MCTS) enabling efficient, adaptive, and intelligent exploitation in both real-world and CTF environments. 🚀 Core Features AI-generated step-by-step attack recommendations Context-aware tool suggestions aligned with vulnerabilities Critical path analysis to maximize impact with minimal noise Autonomous attack chain simulation with dynamic environment modeling This framework helps red teamers, researchers, and ethical hackers adopt a strategic, AI-assisted offensive mindset, moving beyond traditional one-off exploits. 📢 Citation Request If you use PentestThinkingMCP in your research, academic work, or projects, please cite our paper: “LIMA: Leveraging Large Language Models and MCP Servers for Initial Machine Access” – IEEE FMLDS 2025.

Create personas of real people from their public web content. Ask questions and get answers grounded in their actual statements. Switch between personas and revisit saved profiles anytime.

Person lookup from email: name, title, company, social profiles. x402.

MCP server for AI-driven image editing with Photopea