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Why is Christian Science in our name? Our name is about honesty. The Monitor is owned by The First Church of Christ, Scientist, and we’ve always been transparent about that. The church publishes the ...

Show HN: MCP server gives your agent a budget (save tokens, get smarter results)

As a consultant I foot my own Cursor bills, and last month was $1,263. Opus is too good not to use, but there's no way to cap spending per session. After blowing through my Ultra limit, I realized how token-hungry Cursor + Opus really is. It spins up sub-agents, balloons the context window, and suddenly, a task I expected to cost $2 comes back at $8. My bill kept going up, but was I really going to switch to a worse model?No. So I built l6e: an MCP server that gives your agent the ability to budget. It works with Cursor, Claude Code, Windsurf, Openclaw, and every MCP-compatible application.Saving money was why I built it, but what surprised me was that the process of budgeting changed the agent's behavior. An agent that understands the limitations of the resources doesn't try to speculatively increase the context window with extra files. It doesn't try to reach every possible API. The agent plans ahead, sticks to it, and ends work when it should.It works, and we've been dogfooding it hard. After v1 shipped, the rest of l6e was all built with it. We launched the entire docs site using frontier models for $0.99. The kicker was every time l6e broke in development, I could feel the pain. The agent got sloppy, burned through context, and output quality dropped right along with it.Install: pip install l6e-mcpDocs: <a href="https://docs.l6e.ai" rel="nofollow">https://docs.l6e.ai</a>GitHub: <a href="https://github.com/l6e-ai/l6e-mcp" rel="nofollow">https://github.com/l6e-ai/l6e-mcp</a>Website: <a href="https://l6e.ai" rel="nofollow">https://l6e.ai</a>Happy to answer questions about the system design, calibration models, or why I can't go back to coding without it.

Ask HN: What Is Anthropic Doing?

I'm without words with Opus 4.7. This is possibly the biggest quality regression of a computer product since Windows Vista. Or maybe ever.So, here is my question to the community: what is the play here?I don't buy the money angle, since they're about to be bleeding subscribers. I hardly can justify paying for Max anymore and switched to Codex at work first time in months after I spent 4 very frustrating hours trying to get the model to fix the code to my liking.I also don't buy the corporate angle. Models are part of infrastructure, like APIs and the same rule apply to them. Mostly: don't break the integrations. Since new generation of models can completely break output expectations, deploying them becomes organizational effort and support for older ones is abysmal. At some point those organizations will get tired of "adapting" all the time.So what's the play here?

Ask HN: How to get motivation of side projects if you don't need the money?

I have a really good salary as a remote engineer (and I live in a part of the world where one salary could last me 6 months). However, I am getting bored of my work (due to many reasons; AI could be one of them).I want to try different side projects (not all of them being tech-related); for example, opening an online niche bookshop would be ideal. But when I consider the effort I would have to put in and the money I would earn (a small percentage of my salary), I know it's not worth it. It will add stress, consume time, and it won't a good experience anymore. I am also aware that creating a side project that will give me a significant portion of my salary is almost impossible at this point.I know some people say that we should do some things just for the pleasure of it and not for the money, and I agree, but that's only when money is not involved. How can you do it with side projects / side businesses?

Ask HN: What pricing model works for high COGs side project?

If I remember correctly, the $20 plan many of them have would have to cost around $150 to break even.I think it's the nature of these 2 levers of route count + frequency, which can generate such wildly amoutns of cost that makes it hard for me to imagine a world of a flat subscription plans.Looking at other busiensses with comparable price dynamics, I found what I'm calling the "home security camera" model, where they charge a flat rate and +X per camera. Recently a large cam

Telemetry and intent analytics for AI products using natural language

Hey all. About seven months ago, I was building a monetization/adtech tool for AI products. To support it, I built a small telemetry layer on the side mostly for internal usage.I know it's a tired story for many here but .. I never thought it would happen to me. Our old users and most of our new users started to ignore the monetization tool and solely using our telemetry tool. Usage data, support conversations, churn patterns all pointed in the same direction. Six weeks ago we made our intent telemetry tool for the whole product.What I built: A telemetry and intent intelligence layer designed specifically for LLM-based products. It captures what users are actually trying to accomplish, where conversations break down, which intents your model handles well vs. poorly, and how that connects to retention and activation. Any feedback would be great.Documentation: https://docs.atheon-inc.com/Demo: https://www.youtube.com/watch?v=54kusmA9a6c

Show HN: AnyHabit – A minimalist habit tracker for Raspberry Pi and Docker

I wanted something simple without subscriptions or bloat, so I built this to track both positive habits you want to build and negative ones you want to avoid, and it even calculates the money you save from avoiding those bad habits.It's definitely not perfect and is still a very simple app at its core, but since this is my first major open-source launch, I'd really love to get some eyes on it. I'm actively looking for feedback, feature ideas, and pull requests if anyone is looking

Show HN: Anvil – a multi-repo AI pipeline and an MCP server for code search

Hey HN. This is my first time posting here so please be patient with me if I make any mistakes with the format.I want to tell you about Anvil. Anvil is two open-source tools that're in the same repository. They help solve two problems I have been having at my job. At my job I have to work with 5 repositories and we use Kafka and a shared Postgres database.My first problem was that I got tired of explaining my project to Claude every time I started a session. Every time I started a session I would spend the first ten minutes explaining my project pasting files and talking about which services communicate with each other and what Kafka topics we use. The window where I could type would fill up quickly. I would run out of space to do my actual work. It felt like a waste of time and money. I was paying for the information to be repeated over and over.So I built Anvil Pipeline. Anvil Pipeline looks at every repository in my project builds a graph of how everything's connected and automatically detects the relationships between them like Kafka topics and HTTP routes. This graph is then added to every agent call so the agent already knows how my project is set up. I do not have to paste filesThe pipeline runs across all my repositories. Has many stages, including planning, building and validating. Every stage is saved, so if I lose my connection or my laptop goes to sleep it can pick up where it left off. I built this feature because I got frustrated with losing my work when the connection timed out.My second problem was that every time I used an MCP client like Claude Code or Claude Desktop it would suggest functions that do not exist in my code. I also tried using AI code search tools. They were either tied to a specific IDE or required a SaaS backend that I did not want to use.So I built Code Search MCP. It is a MCP server that any client can use.Code Search MCP uses Tree-sitter parsing for 8 languages and has a search function with many tools, including find_callers and find_dependencies. The default embedding provider is Ollama so it is free to use. I also support providers like Voyage and Mistral if you want better results.I spent a lot of time working on indexing, which means that only the parts of the code that have changed are updated. This makes it much faster and more efficient.Both Anvil tools are fully local which means they do not send any information back to me or require you to create an account. They are also source under the MIT license. The dashboard is not very pretty. I ran out of time to work on the design.I would really appreciate your feedback on the following things:Whether the cross-repo detection strategies work for codebases or just mine.-Whether the 8-stage pipeline is too rigid, for how other people work.-Which of the 11 MCP tools are actually useful. I think 2 or 3 of them might not be needed.-You can find the repository here: <a href="https://github.com/esanmohammad/Anvil" rel="nofollow">https://github.com/esanmohammad/Anvil</a>

Ask HN: Is the ongoing AI research driving LLM models to be better?

It looks like OpenAI and Anthropic invest a lot in pre-training (paying Mercor and the like).Also a lot in creating synthetic data, I believe this has bigger AI research involvement and techniques.Of course, there's the RLHF loop that developers using Anthropic/OpenAI products as well, which provides probably yields very good data.This ends up creating the perspective that it is smart, after all, it has been trained with what you want to do, so it can do that for you.But overall, is th

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