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Products that do what Runkite: Self-hosted Agent Control Plane does

Self-hosted agent control plane in one Go binary

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    Hello HN! The day has finally come to stop adding features and start sharing what I've been building the last 5-6 months. It's a bit of CrewAI, OpenDevon, LangFuse/Cloud all in one, providing devs who prefer TypeScript an integrated framework thats provides a lot out of the box to start experimenting and building agents with. It started after peeking at the LangChain docs a few times and never liking the example code. I began experimenting with automating a simple Jira request from the engineering team to add an index to one of our Google Spanner databases (for context I'm the…

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    GitHub: https://github.com/rudderlabs/rudder-server/ === Firstly, a big thanks to the HN community for showing us love and support in our previous HN post (https://news.ycombinator.com/item?id=21081756). At that point, we had just open-sourced the repo and were not fully prepared for a Show HN. We wanted to share updates since then and also do our official Show HN. Updates since Sept 2019 1. Changed the name from Rudder to RudderStack :) 2. API compatibility with Segment 3. Open-source control plane so no dependency on the hosted control plane for…

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    RunAgent eliminates the complexity of AI agent deployment across different frameworks and languages. Today's developers face deployment nightmares with fragmented frameworks (LlamaIndex, LangChain, LangGraph, CrewAI, Letta, Agno, etc.) each requiring different deployment processes, creating unnecessary friction. The Solution: Like MCP (Model Context Protocol), RunAgent provides a standardized approach to agent deployment. Developers simply provide a config file and their agent code - RunAgent handles the rest with REST API and WebSocket (Streaming and non streaming). Our open-source platform…

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    Hi HN, Excited to share Agno, a framework and runtime for multi-agent systems. Think of it as FastAPI for AI Agents. At its core is the AgentOS, a high-performance server/runtime that helps you run and manage AI agents, multi-agent teams, and step-based agentic workflows — all inside your own cloud, with full privacy and no external data sharing. What makes it different • Fast & lightweight — Agents instantiate in ~3μs and use ~6.6 KiB of memory on average (tested on M4 MacBook Pro). • Runtime architecture — Async, stateless, horizontally scalable runtime built on FastAPI. • Integrated…

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    Jul 2026 · github.com

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