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
MCP server for Grafana's observability platform. Enables AI agents to query metrics from Prometheus, search and analyze logs from Loki, query traces, list and manage dashboards, and investigate incidents. Useful for debugging production issues, building monitoring dashboards, and performing root cause analysis with AI assistance across the full Grafana LGTM stack.
Official MCP server for Qdrant vector search engine. Acts as a semantic memory layer enabling AI agents to store and retrieve information using vector similarity search. Supports storing text with metadata, semantic querying, configurable embedding models via FastEmbed, and both cloud-hosted and local Qdrant instances. Useful for building RAG pipelines, code search, knowledge bases, and long-term agent memory.
Official Zapier MCP server that exposes thousands of app integrations and Zap actions to AI agents through a single remote endpoint. Lets agents trigger automations and perform actions across apps like Gmail, Slack, Google Sheets, and Salesforce without building custom integrations, with per-action scoping configured in the Zapier dashboard.
Official Asana MCP server that connects AI tools to the Asana Work Graph. Enables agents to create and update tasks, manage projects and sections, add comments, search work, and summarize project status via a remote OAuth-secured endpoint.
Official Semgrep MCP server for static application security testing. Lets AI agents scan code for security vulnerabilities and bugs, run custom rules, and return findings with severity and remediation guidance, embedding SAST into AI-powered development workflows.
Official MCP server for the Milvus vector database. Lets AI agents create collections, insert vectors, and run similarity and scalar-filtered searches over large-scale embedding data, enabling retrieval and long-term memory for AI applications.
MCP server for Jenkins CI/CD. Enables AI agents to trigger builds, inspect job and build status, stream console logs, and diagnose failing pipelines, bringing continuous integration workflows into AI-powered development environments.
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.
Pulumi's official MCP server for AI-assisted Infrastructure as Code. Wraps the Pulumi Automation and Cloud APIs so agents can preview and deploy stacks, read stack outputs, inspect resources, and look up provider/resource schemas from the Pulumi Registry. Helps developers codify cloud architectures and review infrastructure diffs from within an AI coding assistant.
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?
Добавьте его в открытый реестр, который поддерживает сообщество.