Alternatives
Products that do what Skald – open-source context layer API that runs in your VPC does
Hey HN! We built an open source context layer to power AI agents and apps even in air-gapped infra setups. TL;DR: Use our API (or one of the 6 SDKs) to push context into the Skald platform, and get semantic search and AI chat out of the box. We’ve seen companies spend months building a context layer system internally, only for it to have subpar performance and require active maintenance. Skald gives you the plumbing to get started really fast when building context-aware agents and AI apps (customers have gone to prod in a day with us) but is still highly extensible and configurable to fit…
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Hi HN! Last year the project I launched here got a lot of good feedback on creating speech to speech AI on the ESP32. Recently I revamped the whole stack, iterated on that feedback and made our project fully open-source—all of the client, hardware, firmware code. This Github repo turns an ESP32-S3 into a realtime AI speech companion using the OpenAI Realtime API, Arduino WebSockets, Deno Edge Functions, and a full-stack web interface. You can talk to your own custom AI character, and it responds instantly. I couldn't find a resource that helped set up a reliable, secure websocket (WSS) AI…
2025 · github.com
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2025 · contextch.at
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Excited to share a project I’ve been building for months! Would love to receive honest feedback :) My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong? The product allows you to connect any LLM to any data source with centralized context…
Oct 2025 · github.com
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I've been presenting at local meetups about Context Engineering, RAG, Skills, etc.. I even have a vbrownbag coming up on LinkedIn about this topic so I figured I would make a basic example that uses bedrock so I can use it in my talks or vbrownbags. Hopefully it's useful.
Apr 2026 · github.com
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Howdy y'all, I'm Jesse and I'm pleased to share Rift (https://www.github.com/morph-labs/rift), an open-source AI-native language server for the IDEs of the future. Software will soon be written mostly by AI SWEs working alongside humans. Codebases and the development environments around them will soon become living artifacts that can anticipate, maintain context on, and execute your every intention. Software development is rapidly evolving and key infrastructure like language servers must evolve with it to support a new generation of developer tools. As part of Rift,…
2023 · github.com
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Hi HN, I'm excited to finally launch this project. While existing tools like Postman excel at API discovery and testing, they often require us to navigate complex interfaces, manually construct requests, etc. That's why I created OpenAstra. The core idea is to combine the visual richness of traditional API tools with the simplicity of a chat interface. Think of it as "Postman meets ChatGPT" - allowing us to interact with APIs through natural conversation while retaining core essential features of traditional API tools. If you want to test an endpoint or understand what it does? Just ask. The…
2025 · github.com
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Hi, we're Sohaib and Hannan from APIMatic. We built Context Plugins: given an OpenAPI spec, we generate SDKs and an MCP server that exposes structured API context to AI coding assistants. This gives tools like Cursor access to comprehensive, up-to-date API context (including SDK documentation and API integration patterns), instead of relying on outdated training data or code scraped from GitHub. We've just launched a pilot with PayPal, it's live on the PayPal Developer Portal https://developer.paypal.com/serversdk/java/getting-started/.... In our benchmarks for…
Mar 2026 · apimatic.io
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Hello HN, I created Decispher (decispher.com) to enable human developers and AI agents working alongside each other to share their context. It has some pretty cool features, like Branch Story (explains why a branch's code looks the way it does) and Session Context Transfer (an MCP tool that can copy context from one chat, agent, or machine to another). You can also capture context from engineering platforms like Slack, JIRA, and Git(hub/lab) just by tagging @Decispher.
Jul 2026
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Hey HN! I'm Fabio and I built UltraContext, a simple context API for AI agents with automatic versioning. After two years building AI agents in production, I experienced firsthand how frustrating it is to manage context at scale. Storing messages, iterating system prompts, debugging behavior and multi-agent patterns—all while keeping track of everything without breaking anything. It was driving me insane. So I built UltraContext. The mental model is git for context: - Updates and deletes automatically create versions (history is never lost) - Replay state at any point The API is 5 methods:…
Jan 2026 · ultracontext.ai
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Today we released an open, Valkey-native context layer for AI agents as part of our packages at BetterDB (agent memory, semantic + multi-tier caching, typed retrieval) that run on a Valkey instance no matter where it is - no vendor lock-in. We even started provisioning Valkey instances starting today. Packages are shipped on npm and PyPi. Why we made it: BetterDB originally started as a monitoring and observability platform for Valkey, Redis and any RESP compatible db. This is still the core of the product, but in the process of building this, we kept seeing that one of the fastest-growing…
Jun 2026 · github.com
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We build runtime security for AI agents. The playground started as an internal tool that we used to test our own guardrails. But we kept finding the same types of vulnerabilities because we think about attacks a certain way. At some point you need people who don't think like you. So we open-sourced it. Each challenge is a live agent with real tools and a published system prompt. Whenever a challenge is over, the full winning conversation transcript and guardrail logs get documented publicly. Building the general-purpose agent itself was probably the most fun part. Getting it to reliably use…
Mar 2026 · github.com
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Dear HN Community, I am a long time fan and first-time contributor. I just launched a developer focused semantic search platform and wanted to share it with the community. The idea is simple: upload structured or unstructured documents, select the fields you want to index and tag as metadata, and instantly get a clean search API you can use in your own app. Here is what it currently supports: - Manage your own tenants and projects - Upload .json and .txt files (support for .pdf, .docx, .xlsx, .yml, etc. coming soon) - Expose 3 APIs: search, upload document (embeddings), and delete document -…
2025 · aisearch.vpuna.com
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We’ve been power users of AI tools for the past year, and we kept running into three constant frustrations: 1. Too many subscriptions – Paying separately for OpenAI, Anthropic, Perplexity, and others quickly adds up. 2. Losing memory & context – Switching between models or platforms means you start over each time. 3. Privacy concerns – With most closed-source models, your data may be stored or used for training. That’s not acceptable for sensitive or professional use cases. So we built AgentSea: a private and safer chat interface where you can access the latest models, agents, and tools in…
2025 · agentsea.com
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Hi, I'm working on a project that regroups all best AI (AIaaS) from different providers (GCP, AWS, Azure, DeepL, etc.) in one API (https://github.com/edenai/edenai-apis). I've got asked the question : why aren't you regrouping Open Source models (instead of proprietary APIs) into one repo? Well because it doesn't make sens to deploy and maintain large pytorch (or other framework) AI models (especially for document parsing, image and video moderation or speech recognition) in every solution that wants AI capabilities. So using APIs makes way more sens. Deployed OpenSource…
2023 · github.com
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Hi HN! I develop Monadic Chat, an open-source framework that connects language models to a Linux environment via Docker. It allows AI agents to execute code, run Jupyter notebooks, and perform web scraping in a secure, sandboxed environment. Key features: - Sandboxed environment for AI code execution - Support for multiple language models - Easy integration with existing Docker workflows I built this because I needed a reliable way to let AI agents interact with a real computing environment while maintaining security and reproducibility. Some possible use cases include: - Helping developers…
2024 · yohasebe.github.io
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Hi HN, I'm Kevin. I built ContextVault because I kept running into the same problem with AI tools. Every project accumulated prompts, coding conventions, architectural decisions, examples, and other pieces of context that made the models significantly more useful. The problem was that this information quickly became fragmented. Some lived in ChatGPT Projects, some in Claude, some in Markdown files, some in internal documentation, and some only existed in previous conversations. Late last year, I realized several people on our team were solving the same problems independently because previous…
Jul 2026 · contextvault.dev
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