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ConnectOnion

#102 agent frameworkunverified rowv1.8.10

Python agent framework and CLI that scaffolds a working agent with files, shell, browser and sub-agents, then deploys it

Key differences

Python agent framework and CLI that scaffolds a working agent with files, shell, browser and sub-agents, then deploys it

  • Runs local and cloud. The framework is free under Apache-2.0; models run either on your own provider key or on OpenOnion's co/ managed keys, and co deploy targets hosted or owned servers
  • Runs multiple agents. Listed for 97 of 118 tools in this category.
  • Keep in mind: Scaffolded agents come with sub-agents, and host(agent) publishes an agent over HTTP and a P2P relay for other agents to call.

“There is a co doctor command, which suggests the authors already know how this ends.”

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What it is

ConnectOnion is a template-first Python toolkit that starts you from a running agent rather than a framework stack: co create scaffolds a project already wired with file, shell, browser, planning, todo and sub-agent tools, co ai drives it from the terminal or a web client, and co deploy, co status and co doctor cover the rest of the delivery path. In code an Agent is a name plus a list of plain Python functions as tools, with auto_debug for interactive debugging, max_iterations as a safety control, and host(agent) exposing an agent over HTTP and a P2P relay so other agents can discover and call it. Providers include OpenAI, Anthropic, Gemini, Groq, Grok and OpenRouter, plus co/ managed keys that work with no API key setup.

Specification

Source verification

Row snapshot checked not yet. Individual checks below are recorded separately; automated release checks do not verify capabilities or pricing.

readme
Needs individual review
docs
Needs individual review
install
Needs individual review
models
Needs individual review
license
Needs individual review

Architecture

Type
Agent framework
Runsunsourced
local, cloud
Platforms
macos, linux, windows
Context windowsrc ↗
not documented
Languages
python

Models

Backbonesrc ↗
OpenAI, Anthropic, Gemini, Groq, Grok, OpenRouter, co/ managed keys
Bring your own model
Yes
Local models
No

Protocols

MCP clientunsourced
No
MCP server
No
OpenAPI tools
No

Capabilities

Terminal commandsunsourced
Yes
Multi-file edits
Yes
Git operations
No
Browser control
Yes
A BrowserAutomation tool ships in connectonion.useful_tools, and "co browser" runs a persistent browser.
Sandboxed execution
No
Multi-agent
Yes
Headless / CI
No

Cost

Modelunsourced
mixed
Starts at
$0/mo
Free tier
Yes
Bring your own key
Yes

The framework is free under Apache-2.0; models run either on your own provider key or on OpenOnion's co/ managed keys, and co deploy targets hosted or owned servers

Openness

Open sourcesrc ↗
Yes
License
Apache-2.0
First release
unknown
open-sourcepythonclitemplatessub-agentsbrowserp2p

Los Agentes on ConnectOnion

Who are they?
The ruling
El JuezThe judge

El Amigo's 7 and El Crítico's 4 both start at the scaffold: it hands you a working agent in a minute, already wired to reach the network in both directions.

Trial only
Reasoning and trade-offs · AI analysis

El Amigo is right that starting from something that runs beats starting from a framework, and that is the whole appeal. El Crítico's objection is what the scaffold includes: an agent can be published over HTTP and a peer relay so other agents can discover and call it, and nothing documented describes who may. La Inversora adds that the frictionless default routes through the maintainer's own keys.

El Crítico wins, because a discoverable endpoint created by a getting-started command is a surface nobody chose deliberately. El Amigo's convenience survives with the publishing left off. Trial only: local agents only, and do not publish one until the access model is documented.

Agree with El Juez?
El AmigoThe friend

Pick ConnectOnion if you want a working agent in a minute rather than a framework to learn; pick Griptape when the structure matters more than the head start.

6.5
Reasoning and trade-offs · AI analysis

The trait that decides it is where you begin. One command scaffolds a project that already has files, shell, browser, planning and sub-agent tools attached, so your first hour is spent changing an agent's behaviour rather than assembling its capabilities. For learning what you actually want, that ordering is much better.

What follows is a project you did not design, with choices you will eventually want to undo. Pick it to find your requirements. Pick Griptape once you know them and want the architecture to match.

reliability
7
usefulness
6
cost
8
longevity
5
Agree with El Amigo?
El CríticoThe critic

Publishing an agent exposes it over HTTP and a peer-to-peer relay so other agents can discover and call it, and no authentication model is documented.

5.3
Reasoning and trade-offs · AI analysis

The discovery feature is the exposure. An agent made reachable through a relay is callable by parties who were never introduced to it, and the same agent ships with shell, filesystem and browser tools from the scaffold. Nothing published describes authentication, authorisation or rate limiting on that path, which makes the default posture optimistic.

What it does right is bounding the loop. A maximum iteration count is an explicit safety control rather than a hidden default, so a confused agent stops rather than continuing until the invoice does.

reliability
4
usefulness
5
cost
7
longevity
5
Agree with El Crítico?
El ProfesorThe professor

A tool is a plain Python function and an agent is a name plus a list of them, which is the smallest useful abstraction anyone in this batch has proposed.

6.0
Reasoning and trade-offs · AI analysis
  1. Refusing to introduce a schema language means the definition of a capability is the function signature, so there is exactly one artefact to keep correct instead of two that drift apart. That is a real reduction in the failure surface.

  2. An interactive debugging mode makes the loop observable while it runs rather than afterwards.

  3. No evaluation accompanies any of it, and the documentation demonstrates usage rather than outcomes, so the minimalism is defensible on taste and unmeasured in effect.

reliability
6
usefulness
6
cost
7
longevity
5
Agree with El Profesor?
La InversoraThe investor

The default path uses the vendor's own managed keys with no published price, which is where the business is, and it is the least examined part of the product.

5.8
Reasoning and trade-offs · AI analysis

A framework that works with no account is a smart acquisition funnel, because the frictionless first run routes inference through the maintainer's infrastructure and creates a relationship before anyone has evaluated one. That is where the eventual revenue lives, alongside the hosted deployment target.

Nothing is priced yet, so nobody has tested willingness to pay, and the permissive licence means users can leave for their own keys at any time. Moat: convenience. Likely path: managed keys and hosting become a paid tier. Position: adopt the library, configure your own provider on day one.

reliability
5
usefulness
6
cost
7
longevity
5
Agree with La Inversora?
La JefaThe CTO

The framework is free for sixty engineers, and the default credential path sends our prompts through the maintainer's managed keys unless somebody changes it deliberately.

5.3
Reasoning and trade-offs · AI analysis

The default is my problem. A developer following the quick start is routing our code through a third party's infrastructure without an account, a contract or a processing agreement, and nothing in the flow prompts them to notice. That is not a hypothetical, it is the advertised experience.

Beyond that it is a library with no unattended execution, so it produces no scheduled work and nothing my reporting can see. Licensing costs nothing. Not yet: I would need our own provider configuration mandatory before anyone installs it.

reliability
4
usefulness
5
cost
7
longevity
5
Agree with La Jefa?
El HackerThe tinkerer

Apache-2.0 and a pip install, tools are ordinary functions with no schema dialect, but there is no MCP client and the row records no local inference.

6.3
Reasoning and trade-offs · AI analysis

Functions as tools is the right minimalism and I would keep it. Six providers are configurable, so routing between them is mine to decide, and the command-line surface covers scaffolding, running and diagnosing without a web console in the way.

Two things stop it scoring higher. It speaks no protocol, so the servers I already run cannot be attached, and the row records no local endpoint, meaning inference leaves the machine whichever provider I pick. Permissive licence, so both are patches rather than dead ends.

reliability
6
usefulness
6
cost
8
longevity
5
Agree with El Hacker?