Agno and Hubzoid: which one fits your team?

A team looking for open-source ways to run AI agents on its own infrastructure may well consider both Agno and Hubzoid. Both are Python projects. Both can serve agents in chat tools such as Slack, both speak MCP, the open protocol assistants use to reach tools, and both keep their data in databases you run.

They start from different questions, though.

Agno asks how to build and run an agent platform. Hubzoid asks how a team can put its own knowledge to work through agents it controls.

That difference usually decides which one fits. This comparison describes Agno from its own website and documentation as published in September 2026, with links to the pages each statement comes from, and Hubzoid from its 1.0.1 release. Both projects change quickly, so check the current documentation before you decide.

Agno and Hubzoid at a glance

Here are the main differences in one table. The sections below explain them, with a source for every statement about Agno.

Agno is a toolkit for building agent platforms

Agno's repository describes it as "a framework and runtime for agent platforms" (GitHub (opens in a new tab)), and its website says it is for building "customer-facing and internal agents, teams and workflows" (agno.com (opens in a new tab)). Its documentation organizes the product into three parts.

• The Agno SDK is a Python toolkit for building agents, teams of agents and workflows. Agno lists "30+ providers behind one API" for models and "100+ integrations" for tools (SDK introduction (opens in a new tab)).
• AgentOS is the runtime. In Agno's words, it "serves agents as an API, an MCP server, and through chat interfaces like Slack, Telegram, and WhatsApp." It runs in your infrastructure and writes its state to databases you configure (AgentOS introduction (opens in a new tab)).
• The control plane is a web interface for testing agents, inspecting traces and sessions, managing knowledge and memory, reviewing approvals and running schedules. It connects from your browser to your own AgentOS (control plane (opens in a new tab)).

The SDK also covers memory of user facts and preferences, knowledge search, input and output guardrails, and pausing a run until a person approves a tool call (human approval (opens in a new tab)). AgentOS adds a scheduler and access control based on signed tokens with scopes.

Agno states that the SDK and AgentOS are open source, and its repository uses the Apache 2.0 license. Its pricing page (opens in a new tab) describes a free plan and paid plans that add features such as a live connection to a running AgentOS, team seats and role-based access control.

Hubzoid is a shared Hub for a team's internal agents

Hubzoid is an open-source platform for internal agents, the ones an organization's own people use for their own work. Its center is the Hub: the team's written instructions, reference notes, step-by-step procedures, helper agents and tools, kept together as a folder of plain files that a person who understands the process can read and edit.

The same Hub is used in three ways:

• Chat. Teammates use a web chat, Slack, WhatsApp, Telegram or an API.
• Workflows. Scheduled work, written in plain language or in Python, runs on a schedule or when another system sends an event, on an engine that survives restarts.
• Connected assistants. A person's own assistant, such as Claude Code, Codex or Hermes, connects over MCP and uses the Hub's knowledge and tools with its own model.

Access is granted per Hub and per capability. Sensitive tools run only for people who were granted them, checked in code before the tool runs, and every allow and deny decision is recorded. The Console, part of your own deployment, is where administrators grant access and see usage, estimated cost and runs. All of it, including the Console and the access controls, is open source under the Apache 2.0 license.

One honest limit: Hubzoid 1.0.1 has no step that pauses a tool call for a person's approval.

One starts from the agent, the other from the team's context

Agno starts from the agent program. You write agents, teams and workflows in Python, combine them with storage, knowledge, memory and integrations, and serve them through AgentOS. It is a broad toolkit for building an agent platform or product, including agents that serve customers.

Hubzoid starts from the team's context. The Hub is written so that the people who know the business process can maintain it, and Hubzoid supplies the chat surfaces, scheduled work, access, records and administration around it, for agents used inside the organization.

Agno searches a library, a Hub reads maintained notes

The two projects treat knowledge differently, and the difference is useful.

• Agno's knowledge feature reads documents, splits them into chunks, converts them into vector embeddings and lets the agent search for the relevant pieces. It supports vector, keyword and hybrid search (knowledge (opens in a new tab)).
• A Hubzoid Hub keeps reference material as plain notes the agent reads by name when it needs them, and searches a separate folder of raw material, such as exports, as plain text. When a curator asks the agent to remember something, Hubzoid saves it as a shared note, kept apart from conversation history.

Large document collections suit retrieval. Definitions and rules that a team keeps current suit notes that people edit directly.

Agno's MCP server runs agents, a Hub's lends its context

Both projects can act as an MCP server, but they offer different things through it.

• AgentOS can "expose agents, teams, workflows, and custom tools to MCP clients," and its default MCP tools include running agents, teams and workflows (MCP server (opens in a new tab)). A client can ask AgentOS to do the work.
• A Hubzoid Hub offers its tools, knowledge, procedures and instructions. The connecting assistant does the reasoning with its own model, so the Hub spends no model tokens on that person's behalf. Each call runs under that person's own identity, and sensitive tools follow their grants.

Each fits a different kind of project

Agno is a natural fit when you are building an agent product or platform in Python, including agents that serve customers. It suits a team that wants a broad toolkit with teams of agents, vector knowledge, user memory, approval steps and many prebuilt integrations, and that is comfortable defining and changing agents in code.

Hubzoid is a natural fit when the goal is internal: one team's context reused in chat, in scheduled work and in the assistants people already use. It suits a team where the people who understand the process should be able to change the agent's context without writing code, and where different people need different tools, with each decision checked outside the model and recorded.

They can meet over MCP

Because both speak MCP, they can also work together. Agno documents that its agents can connect to an outside MCP server and send an authorization header (MCP tools (opens in a new tab)). A Hub's MCP endpoint accepts a person's own key, so an Agno agent could use a Hub's knowledge and tools under that person's access, with each sensitive decision recorded in the Hub.

In the other direction, a Hub can connect to remote MCP servers, and AgentOS can serve one. A connection set up for the whole Hub uses one credential for everyone who uses it, so choose one scoped to what every user may do. Neither pairing is covered in Hubzoid's documentation, so test it in your own setup first.

The deciding question is what you are building

Are you building an agent product, or giving a team shared context and capabilities it can maintain itself?

If it is the first, start with a framework like Agno. If it is the second, start from a Hub.

To see how Hubzoid's pieces fit, read the architecture overview or should you build your own agent harness?