Overview of Awesome Remote MCP Servers

The Awesome Remote MCP Servers repository is a curated catalog of high‑quality, production‑ready Model Context Protocol (MCP) servers that can be accessed over the internet. By focusing exclusively on remote services, it addresses a common pain point for developers: the need to securely and effortlessly integrate external tools into AI assistants without managing local infrastructure. Instead of installing packages, compiling SDKs, or exposing sensitive endpoints, developers can simply copy a server URL and begin interacting with sophisticated APIs—whether that’s project management data from Asana, document storage from Box, or issue tracking from Atlassian.

At its core, the server list solves two intertwined problems. First, it provides a vetted source of MCP endpoints that have been evaluated against strict quality criteria: official support, production readiness, active maintenance, robust authentication (OAuth 2.1 or API keys), and proven reliability. Second, it offers a seamless workflow for connecting AI clients—Claude, ChatGPT, Cursor, and others—to these services. Developers can either use an MCP‑ready client that automatically handles authentication flows or embed the server directly into API requests to LLM providers, enabling a unified experience across different platforms.

Key capabilities of the listed servers are expressed in plain language: each entry includes the server’s domain, authentication method, and maintainer. The catalog covers a broad spectrum of categories—project management, software development, document handling, and RAG-as-a-service—so teams can quickly discover the right tool for their domain. For example, Asana’s server exposes task and project data via MCP, allowing an AI assistant to read, update, or create tasks on behalf of users. Similarly, Box’s server gives secure access to stored documents, enabling context‑aware document retrieval and manipulation within a conversation.

Real‑world use cases abound. A project manager could ask an AI assistant to pull the latest sprint backlog from Atlassian and summarize it for stakeholders. A data scientist might leverage Audioscrape’s RAG service to retrieve relevant audio transcripts during a model fine‑tuning session. In customer support, an assistant could fetch ticket histories from Asana and suggest resolution steps in real time. By integrating these remote MCP servers into existing AI workflows, developers gain instant access to live data sources without compromising security or incurring infrastructure costs.

What sets this repository apart is its focus on remote, authenticated MCP servers that are immediately usable from web‑based clients. Unlike self‑hosted solutions that require complex setup, each entry guarantees a secure connection—either through OAuth 2.1 with dynamic client registration or via pre‑generated API keys—and is maintained by the original service provider. This ensures that developers can trust both the reliability of the endpoint and the integrity of the data exchanged, making it an indispensable resource for building production‑grade AI applications.