Considering one way to provide AI support for Haskell development.

[phoityne]

ChatGPT says>
Yes, it is definitely worth considering to use haskell-debug-adapter as the MCP server for intercepting AI support in Haskell development. Here’s why:

Seamless Integration with VSCode: The haskell-debug-adapter is already designed to work with the VSCode debugging interface via DAP. By adding an MCP server layer on top of it, you can create a powerful system that allows AI agents to interact with the debugging process directly, without needing major changes to the VSCode environment.

Real-Time Debugging Support: Using an AI to monitor and influence debugging in real-time can significantly improve the development experience. For example, AI could suggest breakpoints, analyze stack traces, or even assist with code evaluation while debugging, all while interfacing with GHCi through the HDA.

Flexibility with MCP: Since MCP allows for defining tools and functions that can be called remotely, this makes it easy for the AI to dynamically interact with the Haskell environment. The AI could issue commands to inspect variables, evaluate code, or even handle specific debugging scenarios.

Extensibility: Once you have this integration working, it opens up possibilities for more advanced use cases, like automated debugging, complex static analysis, or even integrating with other AI models for code completion, refactoring suggestions, and optimizations based on the debugging context.

AI Support and Customization: You could create specialized AI agents that are tailored to specific Haskell debugging tasks, such as memory profiling or concurrency debugging, by defining custom tools in the MCP server.

Conclusion:
Using haskell-debug-adapter as an MCP server to intercept and interact with AI-driven support during Haskell development is a promising idea. It provides a flexible, extensible, and seamless way to integrate AI into the debugging process. This approach could enhance the overall development experience, reduce debugging time, and improve the efficiency of identifying and fixing issues in Haskell code.

[phoityne]

ChatGPT says>
Here is an overview of the architecture for using haskell-debug-adapter (HDA) as an MCP server for intercepting AI support in Haskell development:

VSCode → <MCP> → HDA → <DAP Partial> → GHCi-DAP

Key Benefits of This Architecture

• Modular Design: The system is modular, allowing each component (like HDA, MCP, GHCi-DAP) to focus on specific tasks, making it easier to maintain, extend, and debug.
• Separation of Concerns: Each layer (e.g., MCP for communication, HDA for managing debugging, GHCi-DAP for interacting with GHCi) has a clear responsibility. This keeps the system clean and scalable.
• AI Integration: The use of MCP allows AI tools to be integrated seamlessly, making it easier to incorporate AI-driven debugging features, such as suggesting breakpoints or evaluating specific parts of code.
• Direct GHCi Integration: With GHCi-DAP directly communicating with GHCi, the debugging process remains tightly coupled with the Haskell REPL, ensuring efficient execution of Haskell code and debugging commands.

Conclusion

This architecture makes it clear that MCP acts as an intermediary between VSCode and HDA, while HDA translates MCP requests into DAP commands, which are passed through DAP Partial to GHCi-DAP, ultimately interacting with GHCi. The modular nature of the system allows flexibility for adding AI-driven features, such as enhanced debugging suggestions.

[phoityne]

ChatGPT says>

VS Code supports MCP servers

As of recent updates, Visual Studio Code officially supports MCP (Model Context Protocol) servers. This allows AI tools, like GitHub Copilot Chat or other AI assistants, to interact with custom external tools over the MCP interface.

You can read the official documentation here:
🔗 https://code.visualstudio.com/docs/copilot/chat/mcp-servers

VS Code supports local standard input/output (stdio) and server-sent events (sse) for MCP server transport. Currently of the 3 primitives (tools, prompts, resources), servers can only provide tools to Copilot's agent mode. The list and descriptions of tools can be updated dynamically using list changed events. VS Code provides servers with the current workspace folders using roots (spec)

🧠 What does this mean?
You can now:

• Build or connect an MCP server to provide custom context and capabilities to the AI.
• Have AI chat directly with tools like linters, compilers, debuggers, or internal APIs.
• Tailor your development workflow by enabling AI to query these tools dynamically and intelligently during development.

📘 In practice:
For example, you could:

• Implement an MCP server that wraps the Haskell Debug Adapter, letting the AI invoke debugging sessions.
• Use AI to ask things like: “Why did this function crash?” or “Show me the value of x in this context.”
• The AI would communicate through VS Code → MCP → Debug Adapter (via DAP) → GHCi, to get the answer.

[phoityne]

VSCode AI Chat is communicating via JSON-RPC with the HDA, which acts as the MCP server.

[phoityne]

The video below demonstrates MCP communication between VSCode and the HDA.
The debugging behavior on the HDA side is purely a dummy implementation – it’s just emulating the debug sequence.

On the HDA side, we’ve exposed three tools to simulate launch, set-breakpoint, and scope.
We provide instruction information to the LLM (GitHub Copilot), guiding it to perform debugging by executing the tools sequentially.

It seems to be working as expected!

hda-mcp-demo_480p.mp4

video

[phoityne]

This video demonstrates MCP communication between VSCode and HDA.
We've released nine tools on the HDA side to support debugging operations.
With a little guidance, AI can now run these tools sequentially to control ghci debugging and retrieve information at the desired execution state.

Whether this experience will prove valuable in the future remains to be seen.

mcp02.mp4

[phoityne]

Implementing functionality to enable the use of pty from the MCP server.
https://github.com/phoityne/pty-mcp-server

With this, the MCP server can directly interact with cabal repl.
It seems possible to debug directly within cabal repl without doing anything too elaborate.
Of course, the AI can use the REPL freely, not just for debugging purposes.

short.mp4