deployment & devops를 위한 엄선된 MCP 서버 컬렉션을 찾아보세요. 2597개의 서버를 탐색하고 필요에 맞는 완벽한 MCP를 찾아보세요.
Connects Anthropic's Claude to video encoding workflows for intelligent error handling and automation.
Enables running a remote Model Context Protocol (MCP) server on Cloudflare Workers with OAuth login.
Enables the use of Model Context Protocol (MCP) servers with Cloudflare Durable Objects, utilizing a Server-Sent Events (SSE) transport layer.
Extends server functionality to operate as a worker by proxying messages to an existing server.
Provides a standardized boilerplate for developing custom MCP server implementations.
Connects web-based LLM chat APIs with local nmstate tools via an MCP server, enabling network configuration management.
Enables AI assistants to interact with Nautobot network automation platforms, providing access to network inventory data.
Integrates with Azure DevOps to manage backlogs, work items, and execute queries via a standardized Model Context Protocol (MCP) interface.
Unifies development best practices across multiple programming languages into a single, comprehensive Model Context Protocol (MCP) server.
Launch new cryptocurrency tokens and manage liquidity on Ethereum and Solana blockchains using an AI-powered natural language interface.
Provides secure access to Kali Linux web penetration testing tools for AI assistants in a controlled Docker environment.
Provides a Model Context Protocol (MCP) server to determine daily production deployment suitability with humorous developer-centric reasons.
Enables AI agents to execute server-side JavaScript and perform operations directly on ServiceNow instances, significantly reducing context bloat.
Converts various document types, including PDF, DOCX, PPTX, and images, into clean Markdown suitable for RAG/LLM workflows on the Apify platform.
Facilitates comprehensive Google Cloud Platform operations by querying logs, monitoring services, and debugging deployments through the gcloud CLI.
Provides an intelligent AI Gateway to ensure reliable and optimized tool calls from large language models.
Orchestrates a comprehensive ecosystem of Model Context Protocol (MCP) servers, enabling large language models to communicate with a wide array of external tools and services.
Provides an observability surface for AI agents to validate code changes and for humans to analyze distributed traces with AI assistance.
Control iTerm2 terminal sessions by reading screen content, executing commands, sending keystrokes, monitoring output, and managing panes.
Enables AI assistants to interact with HarmonyOS projects, devices, and applications through a Model Context Protocol server.
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