I built a debugging MCP server that saves me ~2 programming hours a day
Hi! Deebo is an agentic debugging system wrapped in an MCP server, so it acts as a copilot for your coding agent. Think of your main coding agent as a single threaded process. Deebo introduces multi threadedness to AI-assisted coding. You can have your agent delegate tricky bugs, context heavy tasks, validate theories, run simulations, etc. The cool thing is the agents inside the deebo mcp server USE mcp themselves! They use git and file system MCP tools in order to actually read and edit code. They also do their work in separate git branches which provides natural process isolation. Deebo…
I built a debugging MCP server that saves me ~2 programming hours a day launched on April 25, 2025 with 5 votes and more than 75% of that year's launches.
What it does
In the maker’s words, at launch
Hi! Deebo is an agentic debugging system wrapped in an MCP server, so it acts as a copilot for your coding agent. Think of your main coding agent as a single threaded process. Deebo introduces multi threadedness to AI-assisted coding. You can have your agent delegate tricky bugs, context heavy tasks, validate…
Does a similar job
all alternatives →- Agent 37Mar 2026 · agent37.com · ▲401
Hey HN, I noticed there are 1,000+ MCP skills on GitHub with zero way for creators to charge for them. So I built Agent37. Selling Claude skills today means asking customers to download your skill, set up Claude Code on their laptops, configure MCP servers, and pray it works. No trial, no updates, often you're just handing over the source. Agent37 lets creators upload a skill, share a link, and anyone can try it instantly (no Claude account needed). Built-in Stripe, creators keep 80%. Looking for feedback on the approach. Would you use something like this?
Basin MCP2025 · mcp.basin.ai · ▲168tl;dr - try Basin AI with Cursor/Windsurf, instruction here (https://mcp.basin.ai), and use API key hackernews to gain access. Hey HN — I’m Henry, co-founder of Basin, and I wanted to share something we’ve been working on called Basin MCP, a kind of QA infrastructure for AI coding copilots like Cursor, Windsurf, etc. We built Basin because we kept noticing the same thing: agentic coding tools are great at generating code, but have no idea if the thing they built actually works — or even matches the original intent, and so they're prong to hallucinations. Basically, they have…
Web-eval-agent – Let the coding agent debug itself2025 · github.com · ▲84Hey HN! We’ve been building an MCP server to help AI-assisted web app developers by using browser agents to test whether changes made by an AI inside an editor actually work. We've been testing it on scenarios like verifying new flows in a UI, or checking that sending a chat request triggers a response. The idea is to let your coding agent both code and evaluate if what it did was correct. Here’s a short demo with Cursor: https://www.youtube.com/watch?v=_AoQK-bwR0w When building apps, we found the hardest part of AI-assisted coding isn’t the coding—it’s tedious point-and-click…
VibeShift MCP2025 · github.com · ▲141Hi HN, We are the devs behind VibeShift. We have been building this MCP server to put AI coding assistants in an automatic feedback loop. They code, test, debug, fix everything until we have a fully working, secure code. It tests like a real user, copies network/console and logical errors to give them back to cursor. (1 min demo - https://www.youtube.com/watch?v=bN_RgQGa8B0) We felt this was the natural next step for AI coding assistants. And with new asynchronous assistants like codex, having a plug & play tester makes sure you don't have to spend time debugging and…
Daemons by Charlie LabsJun 2026 · charlielabs.ai · ▲228For almost two years, we've been developing Charlie, a coding agent that is autonomous, cloud-based, and focused primarily on TypeScript development. During that time, the explosion in growth and development of LLMs and agents has surpassed even our initially very bullish prognosis. When we started Charlie, we were one of the only teams we knew fully relying on agents to build all of our code. We all know how that has gone — the world has caught up, but working with agents hasn't been all kittens and rainbows, especially for fast moving teams. The one thing we've noticed over the last 3…
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Hi everyone, I built PyXL — a hardware processor that executes a custom assembly generated from Python programs, without using a traditional interpreter or virtual machine. It compiles Python -> CPython Bytecode -> Instruction set designed for direct hardware execution. I’m sharing an early benchmark: a GPIO test where PyXL achieves a 480ns round-trip toggle — compared to 14-25 micro seconds on a MicroPython Pyboard - even though PyXL runs at a lower clock (100MHz vs. 168MHz). The design is stack-based, fully pipelined, and preserves Python's dynamic typing without static type restrictions.…
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