Openagi is live · free · last verified 8 Nov 2026 · viability monitor
Openagi
OpenAGI is an open-source Python framework for building autonomous AI agents from modular Planner, Worker, and Memory components.
Pick OpenAGI when you want to read and modify the agent loop, not just call one. The component split plus the five shipped templates make it a fast way to learn how planning, memory, and worker delegation actually fit together, and the built-in loop guard removes the most common failure mode in hand-rolled agents. Pass on it for production — AI Planet's own docs concede agents can't remember long or plan far ahead yet.
Verdict generatedVerified 6d ago · liveness 59/100 · cite: rightaichoice.com/tools/openagi
- Python developers who want to inspect and modify agent internals rather than call a black box
- AI researchers experimenting with planning, reasoning, and multi-agent delegation patterns
- Students and hobbyists learning how autonomous agents are structured under the hood
- Teams prototyping an agent concept before committing to CrewAI, LangChain, or LangGraph
- Non-technical users who need a no-code agent builder or visual canvas
- Production systems requiring long-horizon memory or dependable long-range planning
- Teams that need a large library of ready-made connectors on day one
We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.
- Honest verdict, not marketing
- Real pros & cons from real users
- Attributed quotes with receipts
3 free scans · no card needed
Skip OpenAGI if you need an agent that remembers context across sessions or plans many steps ahead — AI Planet's own docs say the current release can't do either reliably enough for production.
Every external system you connect is code you write and maintain, since no pre-built connectors ship with the framework — budget engineering days per integration, not configuration minutes.
OpenAGI is an open-source framework, so there is no licence fee to weigh against alternatives. The cost comparison that matters is engineering time: it is cheaper than commercial agent platforms on licence spend and more expensive than LangChain or CrewAI on setup effort, because those two ship connector ecosystems and community answers that OpenAGI does not yet have.
In short
Openagi — OpenAGI is an open-source Python framework for building autonomous AI agents from modular Planner, Worker, and Memory components. Best for Python developers who want to inspect and modify agent internals rather than call a black box, AI researchers experimenting with planning, reasoning, and multi-agent delegation patterns, Students and hobbyists learning how autonomous agents are structured under the hood. Free to use.
What is Openagi?
Openagi — OpenAGI is an open-source Python framework for building autonomous AI agents from modular Planner, Worker, and Memory components. Best for Python developers who want to inspect and modify agent internals rather than call a black box, AI researchers experimenting with planning, reasoning, and multi-agent delegation patterns, Students and hobbyists learning how autonomous agents are structured under the hood. Free to use.
OpenAGI is an open-source Python framework from AI Planet for developers who want agents that plan, reason, decide, and act instead of just summarizing text. You assemble each agent from named components — Admin, Workers, Planner, LLM, Action, Memory, and VectorStore — and connect them in sequential, parallel, or dynamic communication patterns depending on how your task breaks down. It sits in the same category as CrewAI and LangGraph: a code-first way to wire up multi-agent workflows rather than a no-code canvas. There are two configuration paths. An automated generator scaffolds the config for an agent and its sub-components; manual configuration is there when you want to set each piece yourself. AI Planet also built streamlined integration and configuration handling specifically to kill the infinite agent loops that show up in other orchestration tools. Five working templates ship with the repo so you can see the pieces fit before writing your own: Movie Recommender, JobSearch, Blog Writing, News, and Itinerary Planner. That template set is the fastest way to understand how the Admin/Worker split and the Planner actually behave in a run. AI Planet is upfront about the state of the project — the docs say agents currently "can't remember things for a long time or plan ahead very well." Treat OpenAGI as a prototyping and learning framework rather than a production runtime. It fits Python developers and AI researchers who want the agent loop visible and editable; teams that need long-horizon memory, durable planning, or a no-code builder should look at CrewAI, LangChain, or LangGraph instead.
Key features
- Modular agent architecture: Admin, Workers, Planner, LLM, Action, Memory, VectorStore
- Sequential, parallel, and dynamic agent communication patterns
- Automated agent configuration generation to scaffold new agents
- Manual agent configuration for fine-grained component control
- Built-in loop handling that removes infinite agent loops
- Multi-agent coordination through Admin and Worker roles
- Planner component for task decomposition and reasoning
- Memory component for retaining context across agent interactions
- VectorStore component for retrieval over your own data
- Action component for calling tools and external systems
- Template: Movie Recommender Agent
- Template: JobSearch Agent
- Template: Blog Writing Agent
- Template: News Agent
- Template: Itinerary Planner
Behind the verdict
OpenAGI is one of those frameworks where the honest positioning is buried in the docs: 'we're just starting.' AI Planet publishes that line about agents not remembering things for long or planning far ahead, and I appreciate the candor. It tells you exactly what you're buying: a readable, hackable agent skeleton, not a runtime you'd bet a customer-facing workflow on. Where it earns its keep is learning and prototyping. The Admin/Worker/Planner split is concrete enough to poke at, and the five templates (Movie Recommender, JobSearch, Blog Writing, News, Itinerary Planner) give you a working reference for each pattern instead of a blank Python file. If you're trying to understand why a CrewAI crew behaves the way it does, rebuilding a small version in OpenAGI is a genuinely useful exercise. The loop-handling feature is the sleeper. Infinite agent loops are the classic failure when you hand-roll orchestration — agent A calls B, B calls A, and your token bill climbs. OpenAGI's streamlined configuration is designed to eliminate that, and it's the kind of thing you only notice when you switch to a framework that doesn't do it. Where it bites is anything long-horizon. No durable memory, no dependable long-range planning, no hosted control plane, no vendor SLA. If your agent needs to run for hours or retain context across sessions, you'll spend more time patching OpenAGI than you saved by choosing it. CrewAI and LangGraph have moved further on production concerns; LangChain still has the connector library. We'd reach for OpenAGI as a teaching tool, a research sandbox, or a first pass on a multi-agent idea before you commit to a heavier framework. Skip it if you need a visual builder, a big connector catalog, or something you can put in front of non-technical teammates.
Models under the hood
as of 2026-11-08
Limitations
- OpenAGI is an open-source Python framework from AI Planet for building autonomous agents from modular components (Admin, Workers, Planner, LLM, Action, Memory, VectorStore).
- The DIY framework approach means connecting to external systems and configuring agents requires writing your own code and configuration.
- The live evidence provides no details on model support, deployment process, or hosted platform, so those should be verified directly.
- The provided evidence also contains no information about documentation depth, host system, or community support, so those should not be assumed.
as of 2026-10-08
Researching Openagi? Get your full AI stack in 60 seconds.
Free, no signup — tell us your goal and get tools matched to your budget & existing stack.
Is Openagi still active?
Openagi is live · free · last verified 8 Nov 2026 · viability monitor.
Viability score
How well maintained and how widely used is Openagi? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: November 2026
How we score →What do users say about Openagi?
What people actually say about Openagi — is it worth it?
We scanned public community sources for Openagi on Nov 8, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Only 2 of the posts we fetched could be positively tied to Openagi. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
How we verified this
Every listed fact about Openagi — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 8 Nov 2026. Analysis is drafted with AI models and checked against our editorial standards before publishing; see how we verify.
Verification history
We have re-verified Openagi 14 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed description
- — changed SSL certificate
- — changed our verdict, description, who it suits, who should skip it, summary, features
- — changed limitations, platforms
- — changed link health, hidden costs, who it suits, limitations, who should skip it, switching in, use cases, description, summary, our verdict, switching out, setup time, pricing fit, features
- — changed switching in, hidden costs, limitations, switching out, pricing fit, setup time, who should skip it, use cases
Showing the 6 most recent of 14 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Openagi cost in 2026?
Openagi: Free to use. Pricing last verified 8 Nov 2026.
Where the pricing makes sense
The company stage and team size where Openagi's pricing actually pencils out — and where peers do it cheaper.
OpenAGI is an open-source framework, so there is no licence fee to weigh against alternatives. The cost comparison that matters is engineering time: it is cheaper than commercial agent platforms on licence spend and more expensive than LangChain or CrewAI on setup effort, because those two ship connector ecosystems and community answers that OpenAGI does not yet have.
Has Openagi's pricing changed?
No plan price for Openagi has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Openagi?
Pick Openagi if you are Python developers who want to inspect and modify agent internals rather than call a black box, AI researchers experimenting with planning, reasoning, and multi-agent delegation patterns, Students and hobbyists learning how autonomous agents are structured under the hood, Teams prototyping an agent concept before committing to CrewAI, LangChain, or LangGraph.
Look elsewhere if you are Non-technical users who need a no-code agent builder or visual canvas, Production systems requiring long-horizon memory or dependable long-range planning, Teams that need a large library of ready-made connectors on day one, Anyone who wants a hosted control plane, managed runners, or vendor SLA support.
Skip it if Skip OpenAGI if you need an agent that remembers context across sessions or plans many steps ahead — AI Planet's own docs say the current release can't do either reliably enough for production.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Openagi actually fits — and what changes day-one when you adopt it.
You clone the repo, run the JobSearch template end to end to see how Admin delegates to Workers and how the Planner decomposes the query, then read each component's code to trace where memory is written and dropped.
Outcome: You understand the framework's loop within an afternoon and can make an informed call on whether its memory limits matter for your use case.
You rebuild a research task as two Workers sharing one Planner, switch the communication pattern from sequential to parallel, and compare how task completion changes against a dynamic pattern.
Outcome: You get a controlled comparison of communication topologies without writing the coordination layer from scratch.
You adapt the Blog Writing template's structure into a support-triage agent, letting the automated configuration generator scaffold the setup and then hand-editing the Action component for your internal ticketing API.
Outcome: A working prototype that proves or kills the concept before you invest in a production framework.
Use cases
- Prototype an agent that plans a multi-step task and delegates sub-steps to worker agents
- Study how planning, memory, and action components interact inside an agent loop
- Adapt the Movie Recommender template to your own recommendation domain
- Reuse the JobSearch agent template to match candidates against listings
- Extend the Blog Writing agent to draft and self-edit long-form content
- Build a news curation agent that filters sources by topic
- Turn the Itinerary Planner template into a scheduling or logistics agent
- Model education, finance, or healthcare agent workflows as research prototypes
Setup time & first value
How long it actually takes to get something useful out of Openagi — broken out by persona, not the marketing-page minute.
For a Python developer: minutes to clone the repo and run a shipped template like JobSearch end to end. An hour or two to trace the Admin, Worker, Planner, and Memory components and understand the loop. Half a day to a day to wire your first custom Action against a real external API, since no pre-built connectors exist.
Switching to or from Openagi
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From LangChain: rebuild the chain as Planner plus Workers and move retrieval into VectorStore, keeping your existing prompts mostly intact.
- →From CrewAI: map your crews onto Admin and Workers and reuse the role descriptions as worker configuration.
- →From a hand-rolled agent loop: replace your while-loop and stop conditions with OpenAGI's built-in loop handling and move tool calls into the Action component.
- →From a single-shot LLM prompt pipeline: insert a Planner ahead of the call and give the worker an Action so it can fetch rather than guess.
- ↗To LangChain: port Action components to tools and re-express the Planner as an agent executor chain.
- ↗To CrewAI: translate Admin into a manager agent and each Worker into a crew member with a role.
- ↗To a custom production runtime: keep the component boundaries and reimplement Memory and VectorStore against a persistent store.
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “Openagi”, and we withheld 6: 6 could not be judged, because “Openagi” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Openagi.
Official links
What are the best Openagi alternatives?
The closest alternatives to Openagi we list are CrewAI, Microsoft Agent Framework and TaskWeaver. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| CrewAI | Freemium | Pricing not published | — |
| Microsoft Agent Framework | Paid | Pricing not published | — |
| TaskWeaver | Free | Free | — |
Alternatives to Openagi
View allCrewAI
CrewAI is an enterprise multi-agent platform: visual builder plus a governed control plane for production agent workflows.
Microsoft Agent Framework
Microsoft Agent Framework is an open-source SDK for building agentic AI agents and workflows in Python or C#, now with the GA Agent Harness
TaskWeaver
Microsoft's open-source, code-first Python framework for building stateful, data-intensive conversational AI agents.
Tools that pair well with Openagi
Common stack mates teams adopt alongside Openagi, with the specific reason each pairing earns its keep.
CrewAI
CrewAI is an enterprise multi-agent platform: visual builder plus a governed control plane for production agent workflows.
Microsoft Agent Framework
Microsoft Agent Framework is an open-source SDK for building agentic AI agents and workflows in Python or C#, now with the GA Agent Harness
TaskWeaver
Microsoft's open-source, code-first Python framework for building stateful, data-intensive conversational AI agents.
Openagi vs its closest rival
Openagi's closest head-to-head is with Locus Robotics.
Our Openagi vs Locus Robotics verdict written Jul 3, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
Frequently asked questions
Categories
Best-of guides
For makers of Openagi
- Get a Verified Listing for Openagi ($39): a written decision within 1 working day.
- Free listing for another tool: Free reviews are decided in order, within 3 weeks of the review starting.
Used Openagi? Help shape our editorial sentiment research.