AI · alternatives · 2026
24 alternatives to AgentState – Lightweight state manager for multi-agent AI workflows
AgentState to solve a problem I kept running into: managing state for multi-agent AI systems is surprisingly hard. When you have multiple AI agents that need to coordinate, persist their state, and query each other's status, you typically end up with a mess of Redis/Postgres setups, custom queuing, and manual synchronization code. The whole thing is ~3MB, written in Rust for performance and safety, runs in Docker, and handles 1000+ ops/sec. I've been running it in production for AI workflows and it's been rock solid.
AgentState is a lightweight state manager designed for multi-agent AI workflows that need to coordinate, persist state, and query agent status without complex Redis or Postgres setups. Written in Rust and running in… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 2 we have checked on their own sites, 2 of them free or with a free tier.
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Codex Subagents▲300Parallel custom agents for complex tasks
Mar 2026 · learn.chatgpt.com · its alternatives →
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SimplAIfree tier, from $5/mo▲589Hey HN, I've been building SimplAI for the past several months — it's a platform for building, testing, and deploying LLM-powered agents and multi-step workflows. The problem I kept running into: spinning up an AI agent pipeline means stitching together prompt management, tool calling, memory, evals, and deployment — often from scratch every time. SimplAI tries to be the layer that handles all of that so you can focus on what your agent actually does. What it does: - Visual + code-first workflow builder for chaining LLM calls, tools, and APIs - Built-in prompt versioning and A/B testing…
2025 · simplai.ai · its alternatives →
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AgentSky▲430Any harness, any LLM — cloud-hosted agents on demand.
Aug 2026 · agentsky.dev · its alternatives →
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GraphBit▲437We built GraphBit to solve the reliability gap in AI frameworks. It’s built on a Rust execution core with a Python layer for accessibility — deterministic orchestration, lock-free concurrency, and built-in observability. We’d love feedback from the HN community, especially from those running multi-LLM or agentic workflows at scale.
2025 · graphbit.ai · its alternatives →
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Agentlyfree tier, from $33/mo▲336Agently is an AI Work OS where documents, tasks, team chat, and integrations are fully interconnected, and AI employees operate inside that shared workspace. Instead of prompting AI in isolation, agents can read project context, turn strategy docs into tasks, coordinate with teammates, run research/outreach/content workflows, update boards, and push results back into the system or external tools. The workspace acts as persistent memory, so work continues instead of resetting every prompt. Happy to answer any questions
Jul 2026 · agently.dev · its alternatives →
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Agentic problem solving in its current state is very brittle. I fell in love with it, but it creates as many problems as it solves. I'm Ben Cochran, I spent 20+ years in the trenches with full-stack Engineering, DevOps, high performance computing & ML with stints at NVIDIA, AMD and various other organizations most recently as a Distinguished Engineer. For agents to work reliably you either need massive parameter counts or massive context windows to keep the solution spaces workable. Most people are brute forcing reliability with bigger models and longer prompts. What if I made the problem…
May 2026 · github.com · its alternatives →
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I’ve spent the last two months building AgenticSeek, a privacy-focused alternative to cloud-based AI tools like ManusAI. It runs entirely on your machine—no API calls, no data leaks. Why AgenticSeek? Optimized for local LLMs (developed mostly on an RTX 3060 running deepseek r1 14b). Truly private: All components (TTS, STT, planner) run locally. More responsive than alternatives (we respond fast to issues + active Discord). Designed to be fun—think JARVIS-like voice control, multi-agent workflows, and a slick web UI. Current Features: Web browsing (research + form filling), code…
2025 · github.com · its alternatives →
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Get real-world tasks done with autonomous AI agents
Jun 2026 · arena.ai · its alternatives →
- 10
A deterministic runtime for safe, controllable AI agents
Jul 2026 · solidstatehq.ai · its alternatives →
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com · its alternatives →
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HiveTerm▲86A native workspace for Claude Code, Codex, Antigravity and Grok. Split panes on the desktop, routines in the agent
May 2026 · hiveterm.com · its alternatives →
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AgenticLens▲64Visual debugging, tracing, and replay for agent workflows
Apr 2026 · agenticlens.in · its alternatives →
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Hey HN! A few months ago we shared mcp-agent (https://github.com/lastmile-ai/mcp-agent) [1][2], a lightweight framework that implements every agent pattern from Anthropic’s Building Effective Agents blog [3] and handles MCP server/client management seamlessly. Our core bet is that connecting LLMs to tools, resources, and external systems will soon be MCP-native by default. Today we're launching a significant update: Agents as MCP servers. Currently "agentic" behavior exists only on the MCP client side – clients like Claude or Cursor use MCP servers to solve tasks.…
2025 · github.com · its alternatives →
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Hi HN, Over Thanksgiving weekend I wanted to build an AI agent. As a design exercise, I wrote it as a set of React components. The component model made it easier to reason about the moving parts, composability was straightforward (e.g., reusing agents/tools), and hooks/state felt like a reasonable way to model behavior that changes over time. As I kept experimenting, I realized I was more interested in the framework (and it was a good excuse to explore React’s internals) than in the agent I originally planned, so I built this project instead. In this framework: - Agents are React…
Dec 2025 · github.com · its alternatives →
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It all started with a conversation among friends about limitations in current multi-agent orchestration frameworks. We faced issues like limited control over agent memory and state, complicated persistence, scaling problems, and lack of type safety in Python-based tools. These challenges inspired us to try something different. The result was GraphFlow, a Rust-based lean framework for orchestrating multi-agent workflows that's simple, scalable, and robust. Its key features include: Graph-based orchestration: Easily define workflows using nodes and edges. Lean Execution Engine: A minimal and…
2025 · github.com · its alternatives →
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I've been working on Polign and built a small prototype around something I've been thinking about with agent memory. I have built a lightweight/stateless vector db + BM25 search which works really well with typed facts and structured queries. It uses your own S3, or GCS bucket as primary storage, and restarting a node is fairly quick. Demo + writeup: https://polign.com/blog-edge-agent-memory Live search demo: https://demo.polign.com Docs: https://polign.com
Aug 2026 · polign.com · its alternatives →
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So, it feels like this should exist. But I couldn't find it. So I tried to build it. Agentflow lets you run complex LLM workflows from a simple JSON file. This can be as little as a list of tasks. Tasks can include variables, so you can reuse workflows for different outputs by providing different variable values. They can also include custom functions, so you can go beyond text generation to do anything you want to write a function for. Someone might say: "Why not just use ChatGPT?" Among other reasons, I'd say that you can't template a workflow with ChatGPT, trigger it with different…
2023 · github.com · its alternatives →
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I’ve been tinkering with what a “multi-agent IDE” should look like if your day-to-day workflow is mostly in terminal (Claude Code, OpenAI Codex, etc.). The more I played with it, the more it collapsed into three fundamentals: * A good TUI: Terminal is the center stage, with other stuff (CodeEdit, Diff, Review) baked on the side. I don’t like piping Agent’s output through some electron wrapper, here you get to run CC/Codex/Droid/Amp/etc directly. * Isolation: agents shouldn’t step on each other’s toes. The simplest primitive I’ve found is Git worktrees. It is not as…
Jan 2026 · agentastic.dev · its alternatives →
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Hey all! I recently gave a workshop talk at PyCon Greece 2025 about building production-ready agent systems. To check the workshop, I put together a demo repo: (I will add the slides too soon in my blog: https://www.petrostechchronicles.com/) https://github.com/Aherontas/Pycon_Greece_2025_Presentation_... The idea was to show how multiple AI agents can collaborate using FastAPI + Pydantic-AI, with protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent) for safe communication and orchestration. Features: - Multiple agents running in containers -…
2025 · github.com · its alternatives →
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Build production-ready AI agents in Go.
Nov 2025 · github.com · its alternatives →
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Love OpenClaw? Now ship it to production. Built in Rust.
Feb 2026 · github.com · its alternatives →
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Agentium brings models, memory, tools into one TS runtime.
May 2026 · agentium.in · its alternatives →
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The TLS for autonomous agent state.
Jul 2026 · memora.optitransfer.ch · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →