You Need to Let an AI Manage Your Dev Projects. Here's How.
Z
Zack Saadioui
8/11/2025
You Need to Let an AI Manage Your Dev Projects. Here's How.
Alright, let's talk. You're a developer, you're juggling a million things, & your personal projects (or even some work ones) are in a state of what I like to call "organized chaos." You've got notes in one app, tasks in another, & a vague memory of what you were supposed to be working on last week. It's a mess. I know, because I've been there.
Here's the thing: we're living in the future, & we have AI assistants that are getting SCARILY good. So why are we still manually managing our projects like it's 2010? I recently went down a rabbit hole on this, & what I found is pretty game-changing. Turns out, you can actually set things up so an AI like Claude can act as your very own project manager. No more forgotten tasks, no more context-switching nightmares. Just pure, unadulterated productivity.
And I'm not talking about just asking an AI to write a to-do list for you. I'm talking about building a proper system where the AI has a deep, persistent understanding of your entire project. A system that can track tasks, manage dependencies, & even give you progress reports. Sounds pretty cool, right?
Well, it is. And I'm going to walk you through how it's done. We're going to get a little technical, but I'll break it down. By the end of this, you'll have a clear roadmap to building your own AI project manager.
The Core Idea: What the Heck is a Project Management MCP Server?
So, the magic behind all of this is something called a "Project Management MCP Server." I know, it sounds like a mouthful, but the concept is actually pretty straightforward. MCP stands for Model Context Protocol, & it's basically a way for an AI model like Claude to have a persistent memory & a set of tools it can use.
Think of it like this: normally, when you chat with an AI, it has a limited memory. It might remember the last few things you talked about, but it doesn't have a long-term, structured understanding of your project. An MCP server changes that. It creates a "knowledge graph" of your project – a structured representation of everything from tasks & milestones to team members & risks.
This knowledge graph is the key. It's what allows the AI to "understand" your project on a deeper level. It's no longer just a chatbot; it's a project manager that can:
Maintain Context Continuity: Keep track of project details across multiple planning sessions.
Onboard New Team Members: Quickly get new team members up to speed on project status.
Record Session Results: Document the outcomes of meetings & work sessions.
Honestly, it's like having a junior developer who never sleeps & has a perfect memory.
Now, you might be thinking, "This sounds complicated. I'm just a solo dev working on a side project." But here's the cool part: there are already open-source MCP servers out there that you can use. There's a generic "Project MCP Server" on GitHub that's a great starting point, & there are even specialized versions for tools you're probably already using, like Jira, Trello, & Notion.
This means you don't have to build the whole thing from scratch. You can leverage these existing tools to create your own AI-powered project management system.
How it Works in Practice: A Real-World Example
Let's make this less abstract. A developer on Reddit, who goes by the username bLackCatt79, actually built their own project management MCP server called "ProjectHub-Mcp." And the way they use it with Claude is pretty insightful.
They can literally just talk to Claude in natural language to manage their projects. For example, they can say:
"Create a new project for my React app."
"Break down this feature into tasks."
"How much time am I spending on bug fixes?"
"Generate a progress report for this sprint."
And because Claude is connected to the MCP server, it can actually do these things. It can create the project structure, break down the feature into a detailed task list, query the time tracking data, & generate a comprehensive report. It's not just giving you a generic response; it's interacting with the project's knowledge graph & taking action.
The developer even shared a real example from their workflow. They told Claude, "I'm starting work on user authentication," & the AI:
Created the project (if it didn't already exist).
Broke it down into logical tasks (backend, frontend, testing, docs).
Set up workflow templates.
Started time tracking when they began coding.
This is the power of an MCP server. It gives the AI the tools & the context it needs to be a truly useful project manager.
Getting Your Hands Dirty: The Technical Bits
Alright, so you're sold on the idea. How do you actually build this thing? As I mentioned, you don't have to start from zero. The "Project MCP Server" on GitHub is a fantastic resource. Let's break down what's inside.
The server is built around a few core concepts:
Entities: These are the "things" in your project. The server recognizes a whole bunch of them, like
1
project
,
1
task
,
1
milestone
,
1
resource
,
1
teamMember
,
1
issue
,
1
risk
, & so on.
Relationships: This is how the entities are connected. A
1
task
can be
1
part_of
a
1
project
,
1
assigned_to
a
1
teamMember
, or
1
depends_on
another
1
task
.
Tools: These are the actions the AI can take. There are tools for starting a session, loading the context of a specific entity, creating new entities & relationships, & even getting a high-level overview of the project.
The GitHub repo for the Project MCP Server even provides the code & instructions for setting it up. It's a TypeScript project, but you can run it with
1
npx
or even as a Docker container, so you don't have to be a TypeScript expert to get it working.
Once you have the server running, you need to configure your AI to use it. If you're using Claude Desktop, you can just add a few lines to your
1
claude_desktop_config.json
file to tell it about your new MCP server.
And if you're looking for a business solution to implement this kind of AI automation, a platform like Arsturn can be a great option. Arsturn helps businesses build no-code AI chatbots trained on their own data. While it's often used for customer service, the underlying technology is perfect for this kind of internal project management setup. You could feed it your project documentation, and it would be able to answer questions and provide updates, acting as a centralized knowledge base for your team.
The "No-Code" Alternative: Claude's Native "Projects" Feature
Now, I get it. Not everyone wants to set up their own server. Maybe you're looking for a simpler solution. Well, you're in luck. Anthropic, the company behind Claude, has a built-in feature called "Projects" that can get you a good chunk of the way there, without any of the technical setup.
Claude Projects is basically a dedicated workspace for each of your projects. You can upload all of your relevant documents – reports, data sets, scientific papers, you name it – & Claude will use that as its knowledge base for that specific project. This is HUGE. It means you can have a focused conversation with the AI, & it will have all the context it needs.
Here's what makes Claude Projects so powerful:
Persistent Context: Just like with an MCP server, the context is persistent. You don't have to re-upload your documents every time you start a new conversation.
Custom Instructions: You can give Claude custom instructions for each project. For example, you could tell it to always answer from the perspective of a product manager or to use a specific tone of voice.
Artifacts: This is a really cool feature. Artifacts allow Claude to generate structured outputs, like code snippets, diagrams, or even a marketing campaign dashboard.
So, while it's not as customizable as building your own MCP server, Claude Projects is an incredibly powerful tool for AI-powered project management. And the best part is, it's available on the Pro & Team plans, so it's pretty accessible.
One user described how they use Claude Projects to manage their software development work. They upload technical specifications, design documents, coding standards, & even historical project data. This allows Claude to develop a deep understanding of the project's context, goals, & constraints. They even use it to analyze Figma designs & suggest features based on the UI. Pretty neat, right?
Integrating AI into Your Workflow: Some Best Practices
Whether you decide to build your own MCP server or use Claude's native Projects feature, there are a few best practices that will help you get the most out of your AI project manager.
One developer, Ben Newton, shared a really simple but effective system he uses. He has a single
1
ROADMAP.md
file in his project that serves as the central nervous system. This file contains a prioritized list of tasks, & he's set up his Claude integration to automatically update this file as he works.
Here's how his system works:
Prioritized Sections: The
1
ROADMAP.md
file has sections for "High Priority," "Medium Priority," & "Low Priority" tasks.
Progress Tracking: He uses markdown checkboxes to indicate the status of each task:
1
[ ]
for to-do,
1
[-]
for in-progress, &
1
[x]
for completed.
Automatic Updates: Claude automatically updates the roadmap as he works, moving completed items to a "Recently Completed" section.
This system is brilliant in its simplicity. It provides a clear, at-a-glance view of the project's status, & it offloads the mental overhead of tracking everything yourself.
And this is where a tool like Arsturn could really shine for a business. Imagine having a customer-facing chatbot that not only answers questions but also logs feature requests. These requests could then be automatically added to your internal
1
ROADMAP.md
file, creating a seamless feedback loop between your customers & your development team. Arsturn helps businesses create custom AI chatbots that can provide instant customer support, answer questions, & engage with website visitors 24/7, making this kind of integration a real possibility.
The Future is Now, So Get on Board
Look, the way we work is changing. AI is no longer just a novelty; it's a powerful tool that can augment our own abilities in incredible ways. And project management is one of the areas where it's having the biggest impact.
By setting up a system where an AI like Claude can act as your project manager, you're not just saving time & reducing cognitive load. You're fundamentally changing your relationship with your work. You're creating a system that preserves context, maintains momentum, & helps you make consistent, meaningful progress toward your goals.
Whether you go the full-on technical route & build your own MCP server or start with the more accessible Claude Projects feature, the important thing is to start. Experiment, see what works for you, & don't be afraid to let an AI take on some of the heavy lifting.
Hope this was helpful. I'm still exploring all of this myself, but I'm incredibly excited about the possibilities. Let me know what you think. Have you tried anything like this? What's your setup? I'd love to hear about it.