MCP-серверы

Открытый реестр серверов Model Context Protocol. Находите инструменты, ресурсы и промпты для ИИ-агентов по категории, типу подключения и сценарию использования.

Серверы

177

Инструменты

471

Категории

11

Участники

155

52 сервера

Сортировка
Excel MCP ServerHaris Musa

MCP server for reading and writing Excel workbooks without needing Microsoft Excel installed. Lets AI agents create workbooks and worksheets, read and write cell ranges, apply formulas and formatting, and build charts and pivot tables programmatically. Useful for automating spreadsheet generation, reporting, and data entry from an assistant.

0
Gemini CLI MCP Tooljamubc

An MCP server that lets AI assistants delegate work to the Google Gemini CLI, taking advantage of Gemini's very large context window for whole-file and codebase analysis. Exposes tools to ask Gemini questions with file references, brainstorm ideas, and stream long responses in chunks, so a client model can offload large-context reasoning to Gemini without leaving the current session.

0
Google Drive MCP ServerAnthropic

A Model Context Protocol server for Google Drive that lets AI assistants list, search, and read files stored in Drive, with automatic export of Google Docs, Sheets, Slides, and Drawings to readable formats. Authenticates via OAuth 2.0 and exposes Drive files as MCP resources so agents can ground their answers in your documents without copying data into chat first.

0
Infisical MCP ServerInfisical

Infisical's official MCP server for its open-source secret management platform. Lets AI agents list projects and environments and create, read, update, and delete secrets and folders through controlled tools, so assistants can help manage application configuration without exposing raw credentials in code. Authenticates using a machine identity.

0
JFrog MCP ServerJFrog

JFrog's MCP server lets agents work with Platform services for artifact repositories, build information, release lifecycle management, and software supply-chain workflows.

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MindsDB MCP ServerMindsDB

MindsDB's MCP integration gives agents access to AI workflows, data integrations, and automation capabilities through the MindHub platform.

0
Postman MCP ServerPostman

Postman's official MCP server that connects the Postman platform to AI tools. Gives agents the ability to access workspaces, manage collections and environments, work with API specifications, run requests, and automate API workflows through natural language. Useful for exploring, testing, and maintaining APIs directly from an MCP-compatible assistant.

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Prometheus MCP ServerPavel Shklovsky

MCP server that lets AI assistants query and analyze Prometheus metrics through standardized interfaces. Exposes instant and range PromQL queries, metric and label discovery, and target/health inspection, allowing agents to investigate system performance and troubleshoot incidents using natural language instead of hand-writing PromQL.

0
Shopify Dev MCP ServerShopify

The official Shopify Dev MCP server, built by Shopify, gives AI coding tools direct access to Shopify's developer platform. Agents can search Shopify documentation, explore and introspect the Admin and Storefront GraphQL API schemas, validate GraphQL operations, and scaffold Functions — keeping answers grounded in up-to-date, accurate Shopify APIs.

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Webflow MCP ServerWebflow

Webflow's official MCP server that connects AI tools to your Webflow projects via the Webflow Data API. Lets agents manage sites and pages, work with CMS collections and items, read form submissions, and publish changes, enabling content updates and site automation from an MCP-compatible client.

0

Skills и MCP-серверы

в чём разница?

Skillsописывают, что делать

Skill объединяет инструкции, пример промпта и рекомендуемые модели, чтобы агент стабильно выполнял задачу. Skills добавляют знания, а не новые подключения.

MCP-серверыописывают, как подключиться

MCP-сервер расширяет возможности агента, подключая его к реальным системам: базам данных, API и файлам. MCP добавляет подключения и действия, а не инструкции к задаче.

Простое правило: выбирайте Skill, когда модели нужно хорошо выполнить задачу, и MCP-сервер, когда ей нужен доступ к инструменту или системе. Их можно сочетать: Skill может использовать инструменты MCP-сервера.

Создали MCP-сервер?

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