Model Context Protocol (MCP) has been the talk of the tech world in 2025, promising to unlock the next level of AI’s usefulness. It’s the next stage in autonomous AI, allowing systems to make changes directly to the real world.

Autonomy is just one reason that MCP promises to be such a game-changer, though. It also prevents developers from having to create custom tools for AI systems and development tools alike. Most of us use GitHub, and many use Docker — there’s really no reason to have to create the same tools again and again.

MCP offers a unique opportunity for developers. Not only does it permit AI systems to perform actions and make changes directly, it also promises to eliminate a huge swathe of unnecessary busywork and distractions. For developers, MCP servers can push changes directly to GitHub, update APIs whenever code is changed, or search for local files, documentation, or use different libraries and frameworks without having to leave the AI-driven development environment like Claude or Cursor.

With that in mind, here are ten MCP servers that are having a profound impact on developers’ workflow!

GitHub MCP Server

The GitHub MCP Server is one of the most established, popular, and widely used MCP tools on the market. It lets developers interact with and engage GitHub from their AI or coding environments, which opens up all manner of possibilities. It also permits programmers to optimize their code using suggestions based on code analysis from public GitHub repositories.

GitHub MCP Server also enables AI systems to retrieve code context, letting developers search and engage with their code using natural language. Finally, GitHub MCP Server empowers AI-driven systems to interact directly with GitHub repositories, ensuring that a codebase is always up to date, no matter where it’s deployed.

Docker MCP

Docker MCP lets developers perform Docker operations from their AI environment, making Docker even faster and easier than it already is. It also lets developers engage with their Docker content without having to open an additional command prompt or terminal. Docker MCP lets developers make the most of Docker containers without having to put up with its downsides. Keep in mind, this is a community library, not an official MCP server built by the company Docker, Inc.

Apidog MCP Server

Apidog MCP Server brings AI and APIs together in all manner of novel ways. Most importantly, it lets API developers create APIs directly from their AI-driven coding environment, like Claude or VS Code. But that’s just the start of its usefulness — it also facilitates more advanced functionality like creating SDKs or data transfer objects (DTOs) for a wide range of programming languages.

Finally, like GitHub MCP Server, Apidog MCP Server ensures that your APIs are always up to date and current, modifying the API anytime there’s a change to the code. Considering that it also lets users with limited programming experience create useful, workable APIs, there’s no reason not to at least experiment with Apidog MCP Server.

Sequential Thinking MCP

Sequential Thinking MCP Server is designed to process your code line by line, helping you to think through your development projects thoroughly and systematically. Instead of merely spitting the code out for you, it helps you work through programming problems, acting more as a programming partner or study buddy than a replacement for human programmers.

Sequential Thinking MCP Server is an invaluable tool in learning how to program, as you can describe what you’d like to achieve, and then it breaks the bigger picture down into smaller, more manageable steps. It’s a clever, useful way to bridge the human element with the productivity-boosting properties of AI and MCPs.

Serena MCP

Serena, the coding agent toolkit, provides a language-aware MCP server, allowing developers to boost their productivity no matter what language they’re working in. Serena’s MCP server goes beyond simple coding suggestions and autocomplete — it examines your own codebase to add additional context, making it an ideal bridge between your own code and new libraries and frameworks you’re exploring.

Brave Search MCP

Brave Search MCP Server is for developers who want to add powerful search capabilities for both local files as well as the web without sacrificing privacy concerns. It uses the Brave Search API to add detailed, specific search potential while still respecting user privacy. It also provides the usual benefits of MCP, like adding semantic search capabilities, context, and suggestions for improvements. With extensive filtering and formatting options, allowing you to specify everything from the freshness of search results to pagination settings, you should absolutely consider the Brave Search MCP Server if you want to add search capabilities to your AI ecosystem.

DesktopCommanderMCP

DesktopCommanderMCP is an MCP server that gives you local terminal control. You can use it for code navigation, refactoring tools, and Git operations directly from your desktop, all without costly cloud API token costs. You can also sort through files, optimize code, or perform versioning. Best of all, DesktopCommanderMCP even permits developers to interact with their code using natural language, meaning they can ask their IDE to perform commands or to navigate files in new and novel ways.

Octocode

Octocode is a bridge between your own code repositories and the wider world. Built on MCP, it enables AI coding assistants to analyze public GitHub repositories as well as internal documents to search, interact with, and optimize code using natural language.

For example, you might ask your IDE to refactor all functions using LangChain. Or you could also tell Octocode to analyze your code for flaws you might not even be aware of, also using natural language. Finally, Octocode can eliminate redundant code or data and make an enterprise’s entire code repository and knowledge base publicly available to the whole team.

Supabase MCP Server

Supabase MCP Server connects developers to the Supabase backend, letting your AI coding environment create tables and databases, manage users, and maintain API endpoints. It’s ideal for developers looking to work with or manage databases using AI agents.

Supabase MCP Server also lets you sort through all of your Supabase backend using natural language, opening up your data for your entire team, regardless of programming experience. Best of all, it lets you work with your databases within your existing coding flow, allowing you to interact with your data and databases without disrupting your coding flow.

MCP Compass MCP

MCP servers are constantly being created and updated. Finding the right MCP server for your project can become as much of a job as searching for the right library or pre-made tool. MCP Compass virtually eliminates that problem. MCP Compass is an MCP server for finding other MCP servers, enabling LLMs to find the most relevant servers for whatever you’re trying to achieve. MCP Compass removes the research phase, letting you and your developers get right to testing out the tools and solving your problems.

Enhancing Developer Workflows With MCP Servers

MCP is the next step toward making science fiction science fact. It’s also the next step in unlocking AI’s ultimate potential, which is a continuation of APIs’ mission to democratize access to data and technology. By providing standardized, AI-friendly interfaces to popular platforms like GitHub, Docker, Supabase, and beyond, MCPs remove the barrier between data, everyday tasks, and implementation.

Whether it’s enabling seamless code updates, automating repetitive actions, or enhancing collaboration through natural language interaction, MCPs empower developers to focus on writing and publishing code rather than wasting time on unnecessary clerical or busywork. If AI isn’t going anywhere anytime soon, neither is MCP. So, check out the above MCP servers to get a sense of how compelling this technology can be.