The best Hacker News stories from Show from the past day
Latest posts:
Show HN: We made an MCP server so Cursor can debug Node.js on its own
Show HN: We made an MCP server so Cursor can debug Node.js on its own
Show HN: We made an MCP server so Cursor can debug Node.js on its own
Show HN: FastOpenAPI – automated docs for many Python frameworks
Show HN: FastOpenAPI – automated docs for many Python frameworks
Show HN: FastOpenAPI – automated docs for many Python frameworks
Show HN: Hyperbrowser MCP Server – Connect AI agents to the web through browsers
Hi HN! Excited to share our MCP Server at Hyperbrowser - something we’ve been working on for a few days. We think it’s a pretty neat way to connect LLMs and IDEs like Cursor / Windsurf to the internet.<p>Our MCP server exposes seven tools for data collection and browsing:<p>1. `scrape_webpage` - Extract formatted (markdown, screenshot etc) content from any webpage<p>2. `crawl_webpages` - Navigate through multiple linked pages and extract LLM-friendly formatted content<p>3. `extract_structured_data` - Convert messy HTML into structured JSON<p>4. `search_with_bing` - Query the web and get results with Bing search<p>5. `browser_use_agent` - Fast, lightweight browser automation with the Browser Use agent<p>6. `openai_computer_use_agent` - General-purpose automation using OpenAI’s CUA model<p>7. `claude_computer_use_agent` - Complex browser tasks using Claude computer use<p>You can connect the server to Cursor, Windsurf, Claude desktop, and any other MCP clients with this command `npx -y hyperbrowser-mcp` and a Hyperbrowser API key. We're running this on our cloud browser infrastructure that we've been developing for the past few months – it handles captchas, proxies, and stealth browsing automatically.<p>Some fun things you can do with it: (1) deep research with claude desktop, (2) summarizing the latest HN posts, (3) creating full applications from short gists in Cursor, (3) automating code review in cursor, (4) generating llms.txt for any website with windsurf, (5) ordering sushi from windsurf (admittedly, this is just for fun - probably not actually going to do this myself).<p>We're building this server in the open and would love feedback from anyone building agents or working with web automation. If you find bugs or have feature requests, please let us know! One big issue with MCPs in general is that the installation UX sucks and auth credentials have to be hardcoded. We don’t have a solution to this right now but Anthropic seems to be working on something here so excited for that to come out. Love to hear any other complaints / thoughts you have about the server itself, Hyperbrowser, or the installation experience.<p>You can check us out at <a href="https://hyperbrowser.ai">https://hyperbrowser.ai</a> or check out the source code at <a href="https://github.com/hyperbrowserai/mcp" rel="nofollow">https://github.com/hyperbrowserai/mcp</a>
Show HN: Hyperbrowser MCP Server – Connect AI agents to the web through browsers
Hi HN! Excited to share our MCP Server at Hyperbrowser - something we’ve been working on for a few days. We think it’s a pretty neat way to connect LLMs and IDEs like Cursor / Windsurf to the internet.<p>Our MCP server exposes seven tools for data collection and browsing:<p>1. `scrape_webpage` - Extract formatted (markdown, screenshot etc) content from any webpage<p>2. `crawl_webpages` - Navigate through multiple linked pages and extract LLM-friendly formatted content<p>3. `extract_structured_data` - Convert messy HTML into structured JSON<p>4. `search_with_bing` - Query the web and get results with Bing search<p>5. `browser_use_agent` - Fast, lightweight browser automation with the Browser Use agent<p>6. `openai_computer_use_agent` - General-purpose automation using OpenAI’s CUA model<p>7. `claude_computer_use_agent` - Complex browser tasks using Claude computer use<p>You can connect the server to Cursor, Windsurf, Claude desktop, and any other MCP clients with this command `npx -y hyperbrowser-mcp` and a Hyperbrowser API key. We're running this on our cloud browser infrastructure that we've been developing for the past few months – it handles captchas, proxies, and stealth browsing automatically.<p>Some fun things you can do with it: (1) deep research with claude desktop, (2) summarizing the latest HN posts, (3) creating full applications from short gists in Cursor, (3) automating code review in cursor, (4) generating llms.txt for any website with windsurf, (5) ordering sushi from windsurf (admittedly, this is just for fun - probably not actually going to do this myself).<p>We're building this server in the open and would love feedback from anyone building agents or working with web automation. If you find bugs or have feature requests, please let us know! One big issue with MCPs in general is that the installation UX sucks and auth credentials have to be hardcoded. We don’t have a solution to this right now but Anthropic seems to be working on something here so excited for that to come out. Love to hear any other complaints / thoughts you have about the server itself, Hyperbrowser, or the installation experience.<p>You can check us out at <a href="https://hyperbrowser.ai">https://hyperbrowser.ai</a> or check out the source code at <a href="https://github.com/hyperbrowserai/mcp" rel="nofollow">https://github.com/hyperbrowserai/mcp</a>
Show HN: My Attempt to Organize the World of AI Dev Tools
I've been exploring the (not so=) amazing potential of AI in coding and have compiled a list of tools. From AI-powered IDEs to code generators, this resource is my contribution to the community.<p>I'm still on the fence about including txt2sql projects, as their functionality seems too basic to me.<p>And I'm personally maintaining this, so your feedback is wellcome.
Show HN: Torch Lens Maker – Differentiable Geometric Optics in PyTorch
Hello HN! For the past 6 months I've been working on an open source python library that implements differentiable geometric optics in PyTorch. It's very experimental still, but eventually the goal is to use it to design optical systems with a state of the art optimization framework and a beautiful code based API. Think OpenSCAD, but for optical systems.<p>Not only is PyTorch's autograd an amazing general purpose optimizer, but torch.nn (the neural network building blocks) can be used pretty much out of the box to model an optical system. This is because there is a strong analogy to be made between layers of a neural network, and optical elements in a so-called sequential optical system. So the magic is that we can stack lenses as if we were stacking Conv2D and ReLu layers and everything works out. Instead of Conv2D you have ray-surface collision detection, instead of ReLu you have the law of refraction. Designing lenses is surprisingly like training a neural network.<p>Check out the docs for examples of using the API. My favorite one is the rainbow :) <a href="https://victorpoughon.github.io/torchlensmaker/examples/rainbow" rel="nofollow">https://victorpoughon.github.io/torchlensmaker/examples/rain...</a><p>You should be able to `pip install torchlensmaker` to try it out, but I just set it up so let me know if there's any trouble.<p>I was part of the Winter 1'24 batch at the Recurse Center (<a href="https://www.recurse.com/" rel="nofollow">https://www.recurse.com/</a>) working on this project pretty much full time. I'm happy to talk about that experience too!
Show HN: Torch Lens Maker – Differentiable Geometric Optics in PyTorch
Hello HN! For the past 6 months I've been working on an open source python library that implements differentiable geometric optics in PyTorch. It's very experimental still, but eventually the goal is to use it to design optical systems with a state of the art optimization framework and a beautiful code based API. Think OpenSCAD, but for optical systems.<p>Not only is PyTorch's autograd an amazing general purpose optimizer, but torch.nn (the neural network building blocks) can be used pretty much out of the box to model an optical system. This is because there is a strong analogy to be made between layers of a neural network, and optical elements in a so-called sequential optical system. So the magic is that we can stack lenses as if we were stacking Conv2D and ReLu layers and everything works out. Instead of Conv2D you have ray-surface collision detection, instead of ReLu you have the law of refraction. Designing lenses is surprisingly like training a neural network.<p>Check out the docs for examples of using the API. My favorite one is the rainbow :) <a href="https://victorpoughon.github.io/torchlensmaker/examples/rainbow" rel="nofollow">https://victorpoughon.github.io/torchlensmaker/examples/rain...</a><p>You should be able to `pip install torchlensmaker` to try it out, but I just set it up so let me know if there's any trouble.<p>I was part of the Winter 1'24 batch at the Recurse Center (<a href="https://www.recurse.com/" rel="nofollow">https://www.recurse.com/</a>) working on this project pretty much full time. I'm happy to talk about that experience too!
Show HN: Torch Lens Maker – Differentiable Geometric Optics in PyTorch
Hello HN! For the past 6 months I've been working on an open source python library that implements differentiable geometric optics in PyTorch. It's very experimental still, but eventually the goal is to use it to design optical systems with a state of the art optimization framework and a beautiful code based API. Think OpenSCAD, but for optical systems.<p>Not only is PyTorch's autograd an amazing general purpose optimizer, but torch.nn (the neural network building blocks) can be used pretty much out of the box to model an optical system. This is because there is a strong analogy to be made between layers of a neural network, and optical elements in a so-called sequential optical system. So the magic is that we can stack lenses as if we were stacking Conv2D and ReLu layers and everything works out. Instead of Conv2D you have ray-surface collision detection, instead of ReLu you have the law of refraction. Designing lenses is surprisingly like training a neural network.<p>Check out the docs for examples of using the API. My favorite one is the rainbow :) <a href="https://victorpoughon.github.io/torchlensmaker/examples/rainbow" rel="nofollow">https://victorpoughon.github.io/torchlensmaker/examples/rain...</a><p>You should be able to `pip install torchlensmaker` to try it out, but I just set it up so let me know if there's any trouble.<p>I was part of the Winter 1'24 batch at the Recurse Center (<a href="https://www.recurse.com/" rel="nofollow">https://www.recurse.com/</a>) working on this project pretty much full time. I'm happy to talk about that experience too!
Show HN: A terminal emulator in pure PHP
Show HN: A terminal emulator in pure PHP
Show HN: A terminal emulator in pure PHP
Show HN: A terminal emulator in pure PHP
Show HN: Cursor Directory – From a 3-hour build to a 250k users/mo community
Viktor and I built the first version of Cursor Directory in just 3 hours, right after I watched a few downloaded YouTube videos on my flight to France. The idea was simple: create a single place to find curated rules to enhance the Cursor experience.<p>Fast forward a few months, and the site kept growing. We recently added support for MCPs, a Trending board, the ability to generate your own rules from dependencies, and more!<p>We’d love to hear your thoughts—let us know if you have any ideas to make Cursor Directory even better!<p>Oh, and we’re fully open source!
Show HN: Minimalytics – a standalone minimal analytics app built on SQLite
Hi everyone! I wanted to share my analytics app with you.<p>This project came from requirements to track certain very frequent events. I found that the cost to do it on a regular analytics product was much more than i was willing to pay. Secondly, I also wanted to use as few resources as possible. So I thought it may be a good idea to create something that may be useful for myself (and hopefully others).<p>I have been able to track a great number of events with this using ~20 MB of storage and memory which is incredible. I have been really impressed by golang as a language and as an ecosystem and would love to work more in this language going forward.<p>Some Highlights:
1. No dependencies
2. CLI based management
3. Web based UI (and the server to serve it) included in the program.
4. 20 MB install size.
5. 20 MB memory use while running.
6. Minimal storage requirements because it aggregates events.<p>This can be a great fit for anyone who wants to have a lightweight minimal analytics for internal events.<p>I am looking forward to your comments and feedback.
Show HN: Minimalytics – a standalone minimal analytics app built on SQLite
Hi everyone! I wanted to share my analytics app with you.<p>This project came from requirements to track certain very frequent events. I found that the cost to do it on a regular analytics product was much more than i was willing to pay. Secondly, I also wanted to use as few resources as possible. So I thought it may be a good idea to create something that may be useful for myself (and hopefully others).<p>I have been able to track a great number of events with this using ~20 MB of storage and memory which is incredible. I have been really impressed by golang as a language and as an ecosystem and would love to work more in this language going forward.<p>Some Highlights:
1. No dependencies
2. CLI based management
3. Web based UI (and the server to serve it) included in the program.
4. 20 MB install size.
5. 20 MB memory use while running.
6. Minimal storage requirements because it aggregates events.<p>This can be a great fit for anyone who wants to have a lightweight minimal analytics for internal events.<p>I am looking forward to your comments and feedback.
Show HN: Minimalytics – a standalone minimal analytics app built on SQLite
Hi everyone! I wanted to share my analytics app with you.<p>This project came from requirements to track certain very frequent events. I found that the cost to do it on a regular analytics product was much more than i was willing to pay. Secondly, I also wanted to use as few resources as possible. So I thought it may be a good idea to create something that may be useful for myself (and hopefully others).<p>I have been able to track a great number of events with this using ~20 MB of storage and memory which is incredible. I have been really impressed by golang as a language and as an ecosystem and would love to work more in this language going forward.<p>Some Highlights:
1. No dependencies
2. CLI based management
3. Web based UI (and the server to serve it) included in the program.
4. 20 MB install size.
5. 20 MB memory use while running.
6. Minimal storage requirements because it aggregates events.<p>This can be a great fit for anyone who wants to have a lightweight minimal analytics for internal events.<p>I am looking forward to your comments and feedback.