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Русскоязычный бесплатный MCP-плагин Wildberries: аналитика, конкуренты, SEO, карточки, фото, калькуляторы и прогноз пополнения для Codex и Claude

Enables querying Chatham County, Georgia open geospatial datasets (parcels, addresses, zoning, public works) through ArcGIS Feature Services, with tools to search datasets, query layers, and retrieve layer schema.

Enables AI agents to interact with ConfigCat, a feature flag service for teams.

Pasal ID provides access to the first open, AI-native Indonesian legal database, covering 40,000+ structured regulations from authoritative sources including the Ministry of State Secretariat, Indonesian Audit Board, Constitutional Court, and regional databases. Users can query specific articles, search regulations by type and year, and verify a law's current status—active, amended, or revoked—with citations to primary sources. The server integrates with Claude, Cursor, Windsurf, and ChatGPT.

Lightweight MCP security proxy — compression (up to 86%) + SSRF protection + allow/deny + audit + rate limiting + injection detection

This MCP server implementation provides a bridge between AI agents and the Uber Eats platform. It offers tools for searching menu options and placing food orders through automated browser interactions. The server uses FastMCP and asynchronous programming to handle requests, with background tasks for performing searches and orders. It's designed for use cases where AI assistants need to interact with Uber Eats on behalf of users, streamlining the food discovery and ordering process.

Integrates with the Neptime.io video platform, providing 39 tools for video management, uploads, channels, playlists, comments, articles, and more via the Model Context Protocol.

Enables interaction with Steam: search games, get store details, reviews, prices, discounts, news, and player profiles, libraries, and achievements via the Steam Web API.

Provides access to SmartBear's suite of software quality tools, including BugSnag for error monitoring, Reflect for test automation, Swagger for API development, PactFlow for contract testing, and QMetry/Zephyr for test management. Enables AI assistants to interact with testing workflows, monitor application errors, manage API documentation, and coordinate testing activities across the SmartBear ecosystem.

Enables building and cleaning Delphi projects (.dproj/.groupproj) on Windows using MSBuild with RAD Studio environment initialization. Supports both individual projects and group projects with configurable build configurations and platforms.

A translation server based on MCP architecture, supporting multi-language translation and text-to-speech functionality.

MCP server for newtripoli.xyz (hash-verifiable physics instruments, OCG receipts)

Guardrails for LLM output: pass / fail / review verdicts and one recommended action. Hosted or npm.

Enables secure mailbox access and email management via IMAP/SMTP, with tools for reading, searching, organizing, sending, and deleting emails, designed for local use and compatible with MCP clients like ChatGPT.

Provides real-time and historical weather data for any city worldwide, including forecasts, air quality, and marine conditions, using the free Open-Meteo API.

A local MCP server that provides a safe Google Workspace admin console, enabling AI agents to read users, groups, devices, and reports, with optional write operations gated by explicit confirmation.

Enables querying ABAP programs, classes, function modules, and other objects from SAP systems with OAuth 2.0 authentication.

Enables image generation using Google Gemini models like Gemini 2.0 Flash and Imagen 3.0 with support for custom aspect ratios and negative prompts. It also allows users to list and manage generated images stored in local directories.

An MCP server for managing Incus virtual machines through structured tools for command execution, file management, and snapshot operations. It enables AI agents to puppeteer VMs on a masternode by wrapping the Incus CLI.

Statistics Sweden’s open data made available as an MCP server, using Python and FastMCP