u/Cute_Barracuda_2166

I got tired of re-explaining my API to AI coding agents, so I built a Swagger MCP server.

While working with AI agents, I kept running into the same issue.

Whenever I started a backend-related feature, I had to explain the API again:

• Which endpoints exist
• Request/response structures
• DTOs and schemas
• Authentication requirements

Sometimes I even found myself copying sections from Swagger into the chat.

The bigger problem was when the backend changed. The AI could continue generating code based on an outdated API contract without realizing it.

So I built Swagger Reader MCP and open-sourced it.

It connects to a Swagger/OpenAPI specification and allows AI agents to:

• Discover available endpoints
• Read request and response models
• Explore schemas and DTOs
• Understand API contracts without manual explanation
• Refresh and read the latest spec when the backend changes

It isn't tied to any specific framework or project, so it should work with any API that exposes an OpenAPI/Swagger specification.

For private APIs, authentication is supported through:

• Query parameters
• Custom headers
• Bearer tokens

Credentials stay local and are not sent to any external service.

I've tested it with Cursor, Claude, Codex, and OpenCode.

I'm sharing it because it solved a real workflow problem for me, and I'm curious whether other developers working with AI agents run into the same issue.

Feedback, bug reports, feature requests, and contributions are all welcome.

GitHub and npm links are in the comments.

I got tired of re-explaining my API to AI coding agents, so I built a Swagger MCP server.

While working with AI agents, I kept running into the same issue.

Whenever I started a backend-related feature, I had to explain the API again:

• Which endpoints exist
• Request/response structures
• DTOs and schemas
• Authentication requirements

Sometimes I even found myself copying sections from Swagger into the chat.

The bigger problem was when the backend changed. The AI could continue generating code based on an outdated API contract without realizing it.

So I built Swagger Reader MCP and open-sourced it.

It connects to a Swagger/OpenAPI specification and allows AI agents to:

• Discover available endpoints
• Read request and response models
• Explore schemas and DTOs
• Understand API contracts without manual explanation
• Refresh and read the latest spec when the backend changes

It isn't tied to any specific framework or project, so it should work with any API that exposes an OpenAPI/Swagger specification.

For private APIs, authentication is supported through:

• Query parameters
• Custom headers
• Bearer tokens

Credentials stay local and are not sent to any external service.

I've tested it with Cursor, Claude, Codex, and OpenCode.

I'm sharing it because it solved a real workflow problem for me, and I'm curious whether other developers working with AI agents run into the same issue.

Feedback, bug reports, feature requests, and contributions are all welcome.

GitHub and npm links are in the comments.

I got tired of re-explaining my API to AI coding agents, so I built a Swagger MCP server.

While working with AI agents, I kept running into the same issue.

Whenever I started a backend-related feature, I had to explain the API again:

• Which endpoints exist
• Request/response structures
• DTOs and schemas
• Authentication requirements

Sometimes I even found myself copying sections from Swagger into the chat.

The bigger problem was when the backend changed. The AI could continue generating code based on an outdated API contract without realizing it.

So I built Swagger Reader MCP and open-sourced it.

It connects to a Swagger/OpenAPI specification and allows AI agents to:

• Discover available endpoints
• Read request and response models
• Explore schemas and DTOs
• Understand API contracts without manual explanation
• Refresh and read the latest spec when the backend changes

It isn't tied to any specific framework or project, so it should work with any API that exposes an OpenAPI/Swagger specification.

For private APIs, authentication is supported through:

• Query parameters
• Custom headers
• Bearer tokens

Credentials stay local and are not sent to any external service.

I've tested it with Cursor, Claude, Codex, and OpenCode.

I'm sharing it because it solved a real workflow problem for me, and I'm curious whether other developers working with AI agents run into the same issue.

Feedback, bug reports, feature requests, and contributions are all welcome.

GitHub and npm links are in the comments.

I’ve been trying to enroll in the Apple Developer Program for days and Apple keeps rejecting my enrollment without giving me any real reason.

What happens:

• On the website, I get: “Your enrollment could not be completed at this time.”
• In the Apple Developer app, the “Enroll Now” button is disabled.
• I contacted Apple Developer Support and they replied saying they “can’t continue with my enrollment at this time.”
• When I try to proceed to payment, it just keeps loading forever and never completes.

Things I already checked:

• 2FA enabled
• Correct personal information
• Age above 18
• Valid payment method
• Tried different devices/networks
• Tried both iPhone and Mac
• No VPN

My Apple ID is:

• Fully working
• Can sign into App Store/Xcode normally
• Not banned or locked

I even tried creating a completely new Apple ID, but I still can’t complete the payment (stuck loading) there either.

Apple’s reply was basically:
“For one or more reasons, your enrollment couldn’t be completed.”

No actual explanation.

Did anyone have this exact issue and manage to fix it?
Did you:

• create a new Apple ID?
• wait a few days?
• contact support again?
• get manually approved?

I’d really appreciate any advice because I already have apps/projects I want to publish and this is blocking me completely.

I’ve been trying to enroll in the Apple Developer Program for days and Apple keeps rejecting my enrollment without giving me any real reason.

What happens:

• On the website, I get: “Your enrollment could not be completed at this time.”
• In the Apple Developer app, the “Enroll Now” button is disabled.
• I contacted Apple Developer Support and they replied saying they “can’t continue with my enrollment at this time.”
• When I try to proceed to payment, it just keeps loading forever and never completes.

Things I already checked:

• 2FA enabled
• Correct personal information
• Age above 18
• Valid payment method
• Tried different devices/networks
• Tried both iPhone and Mac
• No VPN

My Apple ID is:

• Fully working
• Can sign into App Store/Xcode normally
• Not banned or locked

I even tried creating a completely new Apple ID, but I still can’t complete the payment (stuck loading) there either.

Apple’s reply was basically:
“For one or more reasons, your enrollment couldn’t be completed.”

No actual explanation.

Did anyone have this exact issue and manage to fix it?
Did you:

• create a new Apple ID?
• wait a few days?
• contact support again?
• get manually approved?

I’d really appreciate any advice because I already have apps/projects I want to publish and this is blocking me completely.

I’m currently building a large SaaS/business system using Flutter.

Current stack:

• Flutter Mobile

I originally planned to use Flutter Web for the operational side too, but after testing larger dashboards/workflows I’m considering Flutter Desktop instead (Windows/macOS).

The app has:

• realtime updates
• websocket/chat usage
• notifications
• forms/tables
• Chart
• dashboard-style UI
• heavy daily usage

I’m mainly targeting:

• Windows
• macOS

For people using Flutter Desktop in production:

• How has the long-term performance been?
• Are there major differences/issues between Windows and macOS?
• How painful are packaging, distribution, updates, signing, and deployment?
• How mature is the package ecosystem today?
• Do you often need to write native/platform-specific code manually?
• How do you usually handle flavors/environments on desktop?
• What would you recommend starting with first?
• Would you still choose Flutter Desktop over Flutter Web for business/internal systems?

Would love to hear real-world experiences and things you wish you know earlier.
Big Thanks.

I've been working on improving my AI workflow to reduce token usage and minimize hallucinations, especially in real production projects.

One thing that helped me a lot is creating a structured/docs folder that contains documentation for almost everything in the project.

For example, my docs folder includes files like:
Architecture.md

Domain.md

Features.md

Navigation.md

Testing.md

Localization.md

Theme.md

Widgets.md

Packages.md

Decisions-Log.md

And I also created a claude md file that acts as an entry point.
The AI reads it first, and from there it knows which docs file to check depending on the task.

This approach helped me:

• Reduce repeated explanations
• Save tokens
• Improve consistency
• Reduce hallucinations significantly

But I feel there are still better workflows out there.

So I have some questions:

• How do you structure project documentation for AI tools?
• Do you split docs into multiple files or keep a single knowledge base?
• Do you use caching, memory layers, or prompt templates?
• Any tools or workflows that significantly reduced token usage?
• Any one use claude obisidian or spec kit development can share his experince?
• How can superpowers help me?