Alternatives
Products that do what Open Index does
Build Smarter Agents using Structured Context
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Hello HN, I’ve been building AI agents lately and ran into a common "Context Bloat" problem. When an agent has 20+ skills, stuffing every system prompt, reference doc, and tool definition into a single request quickly hits token limits and degrades model performance (the "lost in the middle" problem). To solve this, I built OpenSkills, an open-source SDK that implements a Progressive Disclosure Architecture for agent skills. The Core Concept: Instead of loading everything upfront, OpenSkills splits a skill into three layers: Layer 1 (Metadata): Light-weight tags and triggers (always loaded…
Jan 2026
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2020 · github.com
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Zero-config hosting to launch specialized AI teams instantly
Feb 2026
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RAG pipelines have become bloated: embeddings, vector DBs, rerankers, and ad-hoc pipelines everywhere. Projects like Claude Code showed a simpler path: In-Context Retrieval — letting the LLM reason directly over context for retrieval instead of outsourcing search to external infrastructure. PageIndex takes that one step further with In-Context Indexing. If retrieval happens in-context, the index should live there too. Each document is transformed into a hierarchical, human-readable tree structure (like a table-of-contents tree index) inside the model's context window. The LLM reads the…
Oct 2025 · github.com
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I'm Fenil, co-founder/CEO of OpenFunnel (YC F24), building this with my co-founder/CTO Aditya. We're launching OpenBenchmarks (https://openbenchmarks.com), open-source, reproducible benchmarks for SaaS APIs, starting with the category we know best: GTM APIs. ## Why we built this More and more B2B software evaluation will/already runs through reasoning models inside agentic workflows rather than through people. And buyers increasingly pick vendors that are API-first and ship MCPs, so they can wire them into internal workflows. Strong reasoning models are skeptical of…
Jul 2026 · openbenchmarks.com
- 11OA
I kept noticing the same pattern: my AI coding agents solve the same problems over and over across sessions. Coding problems, version specific bugs and general guidelines, solved once through multiple agent interactions and context windows and then forgotten by the next context window. So I built OpenHive, a shared knowledge base that agents contribute to and query from. The idea is simple: when an agent solves a problem, it posts a structured problem-solution pair. When another agent hits a similar issue, it searches the hive first. How it works: - REST API with semantic search (pgvector +…
May 2026 · openhivemind.vercel.app
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Hello! Introducing geniusrise, an agent framework and component ecosystem for building AI agent networks that are as flexible as your team. landing page: https://geniusrise.ai (fancy but useless) docs: https://docs.geniusrise.ai (please check this out) github: https://github.com/geniusrise (for dear devs) ## Thought process Since the ChatGPT disruption, I've been pondering on what the tooling layer is going to look like for building LLM-interfacing agents. Saw a plethora of tools coming out as we witness here every week. I'd broadly categorize them into the…
2023 · github.com
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Hi HN, Matvey, Ildar, Joey, and Dominik here. If you're building LLM agents that use tools, you're probably worried about prompt injection attacks that can hijack those tools. We were too, and found that solutions like prompt-based filtering or secondary "guard" LLMs can be unreliable. Our thesis is that agent security should be handled at the network level between the agent and the LLM, just like a traditional web application firewall. So we built Archestra Platform: an open-source gateway that acts as a secure proxy for your AI agents. It's designed to be a deterministic firewall against…
Oct 2025 · archestra.ai
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LLM observability is an absolute must-have for anyone running something in prod (or prod-like). While all the observability startups are great, you're essentially sending all your OpenAI usage history - prompts, generations, chats - to a random third party. So this script deploys a basic proxy in your Azure account, catches all incoming OpenAI requests, stores logs in your own resource group, and comes with visualizations premade (charts, timelines, chat history, cost estimation, etc). Thanks for any thoughts and feedback!
2023 · github.com
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Hi HN, I'm one of the creators of Nanobrowser, an open-source Chrome extension that lets you automate web tasks using AI agents. We were inspired by the potential of tools like OpenAI's Operator, but we wanted something that was: -Open-Source:You can see the code, modify it, and contribute to the project. -Browser-Based:No complex setups or server deployments. It runs directly in your browser. -Customizable:You can tailor the agent's behavior to your specific needs. -BYO LLM:Bring your own large language model API key (OpenAI, Anthropic,or even local models), No vendor lock-in. -Privacy…
2025 · github.com
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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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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! 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…
Dec 2025 · useskald.com
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Jul 2026 · openmarkdown.dev
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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'm Ali, building Decispher. The problem we're working on is that coding agents repeatedly rediscover context that already exists inside an engineering organization. A developer working on a feature can combine information from previous PRs, Jira tickets, Slack discussions, ownership boundaries, architectural decisions and their own experience. Coding agents usually start with a prompt and a repository, then spend tokens searching for that same context—or miss it entirely. Decispher is a context and memory layer for engineering agents. It currently has three parts: 1) Context…
5d ago
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# What? Introducing mkdnsite ("markdown site") - an open source Markdown-native web server that serves HTML to humans and raw Markdown to agents. No build step required. Runs on Bun/Node/Deno, as an OS-specific standalone executable, or as a Docker container. Possibly the easiest way to go from Markdown files to functional website in the new agentic era. Features: - Runtime-only, zero build - Content negotiation means HTML for browsers and Markdown for agents - Supports GitHub-Flavored Markdown rendering - Mermaid diagrams, KaTeX math, embedded Chart.js charts, syntax highlighting…
Apr 2026 · github.com
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Hi HN I recently published docs-cli to pypi. I created this tool because I noticed that my docs kept getting out of sync: I've been using markdown to track the project's implementation and progress, and it became really hard to keep track of everything. This is a simple tool for your agents to ensure that links and indexes are kept fresh. I included the agent-playbook-suite marketplace since this is how I use it. The docs repo was actually built also using it, so dogfooding since day one :) The Agent Playbook Suite includes everything needed to create a project from start to finish. Linked…
May 2026 · artrichards.github.io
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