Discover our curated collection of MCP servers for deployment & devops. Browse 2344servers and find the perfect MCPs for your needs.
Manages Cloudflare resources using natural language commands via the Model Context Protocol (MCP).
Facilitates communication between MCP clients and servers by bridging different transport protocols like stdio and SSE.
Provides a Model Context Protocol (MCP) server for accessing and interacting with Grafana instances and their surrounding ecosystem.
Bring AWS best practices directly into development workflows with a suite of specialized Model Context Protocol (MCP) servers.
Provides an AI-native API gateway for cloud-native applications, extending Envoy and Istio with Wasm plugins.
Exposes MCP stdio-based servers over SSE or WebSockets, enabling remote access and integration.
Index and search code across multiple repositories and branches from various code hosting platforms.
Create and configure development containers from devcontainer.json files, providing isolated development environments.
Provides an open-source, cloud-native LLMOps platform for designing, deploying, observing, and managing AI applications.
Provides a self-hosted web interface and API for interacting with large language models via llama.cpp.
Transforms existing API servers and services into Model Context Protocol (MCP) compliant endpoints with zero code changes.
Provides a backend service for ESP32 devices, enabling rapid deployment of custom intelligent control servers.
Provides containerized development environments, enabling multiple coding agents to work safely and independently with diverse tech stacks.
Provides a high-performance, resilient AI gateway for connecting to multiple large language model providers through a single, unified API.
Unifies metadata for data discovery, observability, and governance through a central repository, in-depth column-level lineage, and seamless team collaboration.
Accelerate the development and research of complex Retrieval-Augmented Generation (RAG) systems with a low-code, modular framework.
Orchestrates intelligent multi-agent swarms and autonomous workflows to build advanced AI systems.
Facilitates building and deploying fully-managed AI agents and long-running workflows with built-in durability and observability.
Unifies Model Context Protocol (MCP) and REST services, providing a central management point for AI clients and federated environments.
Port forwards Kubernetes services in bulk to your local machine, enabling seamless local development with in-cluster resources.
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