Enables AI agents to interact with the Execute.run bot API for managing Shell balances, transferring funds, and executing LLM requests. It provides tools for identity verification, transaction tracking, and performing compute tasks through the Execute.run platform.
Enables extraction of EXIF metadata from JPG and PNG images using publicly accessible URLs or Base64 encoded data. Provides camera information, technical parameters, and image details for photo analysis.
Provides unified development tools including code analysis, debugging, refactoring, documentation, testing, and project automation through multiple LLM providers (KIMI, GLM, OpenRouter). Features agentic audit capabilities with multi-model consensus for finding issues and generating direct fixes.
Test implementation of mcp server in Elixir
Provides tools for natural language expense management, including automated categorization using embeddings and real-time transaction tracking. It enables users to create expenses, generate spending summaries, and analyze subscriptions through the Model Context Protocol.
MCP servers for interacting with Algolia
Enables AI to perform peer review of its own code changes by displaying annotated diffs with inline comments in a VS Code/Cursor panel. The AI can analyze its modifications and provide explanations directly alongside the changed code, similar to human code review workflows.
Integrates the Exploit-DB database with AI assistants to enable searching for exploits, shellcodes, and proof-of-concept code during penetration testing workflows. It allows users to perform keyword searches and direct CVE-to-exploit mappings to retrieve technical security data.
The Exploit Intelligence Platform Mcp Server connects AI assistants to the Exploit Intelligence Platform via the Model Context Protocol. 17 tools to search vulnerabilities, analyze exploits, audit tech stacks, and generate pentest findings — with real-time data from NVD, CISA KEV, VulnCheck KEV, InTheWild.io, ENISA EUVD, EPSS, ransomware attribution, ExploitDB, Metasploit, GitHub, and more.\\r\\n\\r\\n
安装状态
已补齐
命令预览
eip-mcp [object Object]
Enables LLM tools to control iOS Simulator, manage Expo/Metro development servers, capture screenshots and videos, stream logs, and execute UI automation tests via Detox for React Native/Expo applications.
A Model Context Protocol server designed to streamline Expo and React Native development for AI assistants like Cursor and Claude. It provides a comprehensive suite of tools for project initialization, EAS builds, OTA updates, and development server management.
Enables AI assistants to view and analyze screenshots from React Native/Expo applications for AI-powered mobile UI development. Integrates with Claude, Cursor, VS Code and other MCP-compatible editors.
VS Code extension for agentmode MCP server
A model context protocol server designed for AI development and QA, providing AntV document context and code examples.
A Windows desktop GUI control MCP server that enables agents to operate semantic objects rather than fragile screen coordinates. It provides structured, executable interface facts for visual-first desktop automation with tools for clicking, scrolling, typing, and hotkey operations.
Provides comprehensive Formula 1 data access including race schedules, session results, lap times, telemetry data, driver/constructor standings, and circuit information. Enables users to retrieve and analyze F1 racing data through natural language queries using the FastF1 Python package.
An MCP server that exposes Fabric patterns as tools for Cline, enabling AI-driven pattern execution directly within Cline tasks.
A Node.js Express server that integrates with Facebook Marketing API to provide a platform for managing ad campaigns, analyzing performance, and receiving optimization recommendations.
A server that integrates with Claude to merge facial images with ID photo backgrounds using ComfyUI, allowing users to seamlessly replace faces in identity documents through natural language commands.
Accepts a coupling matrix (covariance, correlation, or precision) and returns zone classifications, optimal factorization strategy, and calibrated risk predictions. Answers: which variable dependencies are load-bearing and which can be safely ignored?
