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Integrates with Fivetran's REST API to manage data pipelines through natural language. Supports listing and managing connections, triggering syncs, viewing schemas and tables, monitoring sync status with task and warning details, and managing destination groups. Built with Python and installable via PyPI.

A local MCP server that enables AI tools to query Obyte blockchain data including balances, units, autonomous agent state and dry runs, and token symbols, supporting both mainnet and testnet.

MCP server providing 37 developer tools for hashing, encoding, regex, JSON, SQL, cron, QR codes, UUID, JWT, and more, all powered by bmobot.ai APIs.

SEC Fails-to-Deliver (CNS fails data).

Enables searching documents in a Tropicalia project using hybrid, neural, or keyword strategies, with optional AI-generated answers and source inclusion.

Create German invoices (§14 UStG) via Claude or any MCP-compatible AI by describing the invoice in natural language.

Records all MCP tool interactions in a centralized ledger, enabling developers to trace, replay, inspect, and audit AI agent workflows.

Generates weekly review reports in Markdown format based on AI session data and optional user annotations.

A tab-aware Playwright MCP server that enables multiple agents to operate on different tabs concurrently while sharing a single browser context and login session.

This GitHub Kanban MCP server, developed by Sunwood AI Labs, integrates GitHub issues management with a Kanban-style workflow. It leverages the GitHub API to provide AI assistants with capabilities for creating, updating, and organizing issues across project boards. The server abstracts the complexities of GitHub's REST API, offering a streamlined interface for issue tracking and project management tasks. By connecting AI systems with GitHub's collaborative features, this implementation enables assistants to automate project workflows, prioritize tasks, and maintain an organized development process. It is particularly useful for software development teams looking to enhance their project management with AI-driven insights and automation.

A Model Context Protocol (MCP) server that provides programmatic access to the Supabase Management API. This server allows AI models and other clients to manage Supabase projects and organizations through a standardized interface.

MCP server that exposes Alpaca Market Data & Broker API as tools, enabling access to financial data like stock bars, assets, market days, and news through the Message Control Protocol.

Provides FFmpeg integration with tools for video cutting, format conversion, video concatenation, silence removal from audio, image-to-video conversion, and raw FFmpeg command execution. Self-contained with bundled FFmpeg binary requiring no separate system installation. Supports common formats including mp4, mp3, wav, and mov.

Universal email integration for AI assistants, supporting any IMAP provider with 18 tools for reading, sending, managing, and automating emails.

A file system MCP server that confines AI assistant file tools to a single folder, with read-only by default and optional write access.

MCP server for vulnerability assessment — searches NVD, CISA KEV & GitHub PoCs with RAG-powered semantic search over HackTricks & PayloadsAllTheThings.

BetsAPI MCP — wraps BetsAPI (betsapi.com) sports events + odds.

MCP server providing AI assistants with safe, read-only SQL Server access

Provides a human-in-the-loop feedback collection system for AI-assisted development tools like Cursor, Cline, and Windsurf through an Electron-based GUI that launches on-demand to gather user input. Built by Tuan Dinh using Electron and the Model Context Protocol SDK, the implementation features a single feedback_loop tool that spawns a draggable, always-on-top window with customizable quick feedback options, free-form text input, and keyboard shortcuts for efficient interaction. The system captures user feedback through a glass-effect interface positioned strategically on screen, returns structured JSON responses with timestamps and project context, and automatically handles window lifecycle management including proper cleanup on cancellation, making it valuable for development workflows requiring human oversight of AI-generated code changes, interactive debugging sessions where developer input guides AI decisions, and collaborative coding environments that benefit from real-time human feedback integration.

caniuse MCP — browser feature support tables