Show HN: Self-updating MCP server for official pip, uv, poetry and conda docs

Using Podman, Compose and BuildKit

Show HN: Modelence – Supabase for MongoDB

Show HN: Modelence – Supabase for MongoDB Hi all, Aram and Eduard here - authors of Modelence (<a href="https://github.com/modelence/modelence" rel="nofollow">https://github.com/modelence/modelence</a>), an all-in-one backend platform for teams that love TypeScript + MongoDB. Think Supabase, but for MongoDB: auth, cron jobs, email, monitoring, without glue code before you can ship.As Karpathy (and many of us) noted, getting from prototype to production is mostly painful integration work. The pieces exist, but stitching them together reliably is the hard part: <a href="https://x.com/karpathy/status/1905051558783418370" rel="nofollow">https://x.com/karpathy/status/1905051558783418370</a>. YC AI Startup School talk about this - <a href="https://www.youtube.com/watch?feature=shared&t=1940&v=LCEmiRjPEtQ" rel="nofollow">https://www.youtube.com/watch?feature=shared&t=1940&v=LCEmiR...</a>We intend to fill those gaps! What you get out of the box:- Authentication / user management- Database- Email integration (3rd party, but things like user verification emails work out of the box)- AI integration- Cron jobs- Monitoring / Telemetry- Configs & secrets- Analytics (coming soon)- File uploads (coming soon)How it runs: A Node.js backend with MongoDB. It's frontend-agnostic, so you can use our minimal Vite + React starter or drop Modelence behind an existing Next.js (or any) frontend.We're also building a managed cloud, similar to what Vercel is for Next.js, except Modelence focuses on the backend instead of the frontend (Vercel is great for content sites like landing pages, blogs, etc, but things like persistent connections and complex backend logic outgrow it quickly). You can find a quick demo here: <a href="https://www.youtube.com/watch?v=S4f22FyPpI8" rel="nofollow">https://www.youtube.com/watch?v=S4f22FyPpI8</a>We're looking for early users (especially TS teams on MongoDB). Tell us what's missing, what's confusing, and what you'd want before trusting this in prod. Happy to answer anything!

Show HN: AgentMail – Email infra for AI agents

Show HN: AgentMail – Email infra for AI agents Hey HN, we're Haakam, Michael, and Adi. We're building AgentMail (<a href="https://agentmail.to/">https://agentmail.to/</a>), an API to give AI agents their own email inboxes. We’re not talking about AI for your email, this is email for your AI.We started building email agents because they can converse with users in their inboxes, automate email-based workflows, and authenticate with third-party applications. Given these unique capabilities, we think email will be a core interface for agents.But we were building on top of Gmail, which was a struggle: poor API support, expensive subscriptions, rate limits, sending limits, GCP Pub/Sub, OAuth, crappy keyword search, and an overall terrible developer experience.Gmail and other providers didn’t work for us. So we decided to bite the bullet and build our own.AgentMail is like Gmail, but API-first, with programmatic inbox creation, events over webhooks and websockets, simple API key auth, organization-wide semantic search, structured data extraction, and usage-based pricing that scales with emails sent/received.Here’s a demo of building an email agent: <a href="https://youtu.be/1V7BISeFUTM" rel="nofollow">https://youtu.be/1V7BISeFUTM</a>, and here’s a demo of a voice agent with its own email inbox: <a href="https://youtu.be/eG2fCsRK4RY" rel="nofollow">https://youtu.be/eG2fCsRK4RY</a>So far AgentMail has been deployed to use cases such as apps with dedicated inboxes for each user, voice agents that receive documents in real time, automated account provisioning and QA testing, cold outbound platforms with thousands of inboxes, automations for processing invoices, and agents that coordinate work with humans and other agents.We would love to hear your thoughts and feedback. You can try our playground at <a href="https://chat.agentmail.to">https://chat.agentmail.to</a>

Show HN: Nia – MCP server that gives more docs and repos to coding agents

Show HN: Nia – MCP server that gives more docs and repos to coding agents Hi HN, I’m Arlan, and I built Nia (<a href="https://www.trynia.ai" rel="nofollow">https://www.trynia.ai</a>), an open MCP that integrates with coding agents like Cursor, Continue, and Cline so they can retrieve external knowledge better than current approaches.Coding agents generate code well but lose accuracy when the answer lives outside the repo in front of them. Developers end up pasting GitHub links, docs, and blog posts by hand and hoping the agent scrolls far enough. Long context windows help, but recent “context rot” measurements show quality still drops as prompts grow. For example, in LongMemEval, all models scored much higher on focused (short, relevant) prompts (~300 tokens) than on full (irrelevant, 113k tokens) prompts, with performance gaps persisting even in the latest models (<a href="https://research.trychroma.com/context-rot" rel="nofollow">https://research.trychroma.com/context-rot</a>).Nia is a MCP that gives more context to any coding agent or IDE. It Indexes multiple repos and docs sites and makes this available via MCP to your coding agent so it has much more context to work with, giving you more specific and accurate answers.Nia uses a hybrid code search architecture that combines graph-based structural reasoning with vector-based understanding. When a repo or documentation is ingested, Tree-sitter parses it into ASTs across 50+ languages and natural languages, and the code is chunked by function/class boundaries into stable, content-addressable units. These chunks are stored both in a graph db to model relationships like function calls and class inheritance, and in a vector store. At query time, a lightweight agent with give_weight tool dynamically assigns weights between graph and vector search based on intent (e.g., "who calls X" vs "how does auth work"), and both paths are searched in parallel. Results are fused, enriched with full code context, and passed through multi-stage rerankers: semantic reranker, cross-encoders, LLM-based validators.Early Signal: In internal evals we improved Cursor’s performance by 27 % once Nia had indexed external docs models couldn’t get from their training data or searching the web.Quickstart: <<a href="https://www.youtube.com/watch?v=5019k3Bi8Wo" rel="nofollow">https://www.youtube.com/watch?v=5019k3Bi8Wo</a>> Demo: <<a href="https://www.youtube.com/watch?v=Y-cLJ4N-GDQ" rel="nofollow">https://www.youtube.com/watch?v=Y-cLJ4N-GDQ</a>>To try it out: grab an API key at <a href="https://app.trynia.ai/" rel="nofollow">https://app.trynia.ai/</a> and follow instructions at <a href="https://docs.trynia.ai/integrations/nia-mcp" rel="nofollow">https://docs.trynia.ai/integrations/nia-mcp</a>.Try it and break it! I’d love to know which contexts your agent still misses. Corner cases, latency issues, scaling bugs. I’m here 24/7.Thanks!

HNSW as abstract data structure: video intro to Redis vector sets

Show HN: I rewrote an outdated React Native map clustering library

Show HN: I rewrote an outdated React Native map clustering library Hey Hacker News,I'm a long-time lurker and wanted to share a project I just finished building.Like many React Native developers, I needed to add marker clustering to a map in my app. The most popular library for this, react-native-maps-clustering, was fantastic in its day but has become outdated and no longer works with modern versions of Expo, React Native, and their dependencies.After hitting a wall of compatibility issues, I decided to take on the challenge of rewriting it from the ground up, focusing on a modern toolchain and a better developer experience.The journey was a lot more challenging than I anticipated. It turned into a deep dive into solving dependency hell with different versions of @types/react, wrestling with build tool configurations for pnpm, bob, and ESLint, and ensuring everything was strictly typed with TypeScript. It felt like a classic case of yak shaving, but I was determined to create a solution that "just works" for developers today.The result is RN Super Cluster, a performant, fully-typed, and easy-to-use clustering library for react-native-maps.What it does: It provides a <ClusteredMapView /> component that you can use as a drop-in replacement for the standard <MapView />. Any <Marker /> components you place inside will be automatically clustered.Key Features:<pre><code> Modern & Maintained: Built with a modern toolchain and designed to be actively maintained. Fully-Typed: Written entirely in TypeScript to prevent common errors and improve autocompletion. High-Performance: Uses supercluster under the hood for extremely fast geospatial clustering. Spiderfier: At the maximum zoom level, overlapping markers automatically "spiderfy" (spread out on a spiral) so they can be individually tapped. Customizable: You can provide your own custom components for rendering clusters, and callbacks for handling press events. </code></pre> This was a passion project born out of necessity, and I hope it can save other React Native developers the headaches I went through.I would love to get your feedback, and contributions are more than welcome!GitHub: <a href="https://github.com/suwi-lanji/rn-maps-clustering">https://github.com/suwi-lanji/rn-maps-clustering</a> NPM: <a href="https://www.npmjs.com/package/rn-maps-clustering" rel="nofollow">https://www.npmjs.com/package/rn-maps-clustering</a>Thanks for checking it out!