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Codel

#257 overall#19 autonomous sweverified Sep 4, 20260.2.2

Self-hosted autonomous agent with a terminal, browser and editor, each task running in its own Docker container

Key differences

Self-hosted autonomous agent with a terminal, browser and editor, each task running in its own Docker container

  • Runs local and sandbox. Free and open source, self-hosted; you supply an OpenAI key or point it at a local Ollama server
  • Runs local models. Listed for 7 of 24 tools in this category.
  • Includes a Docker sandbox. Listed for 16 of 24 tools in this category.

“It picks the Docker base image from your task description, which is either clever or how you end up compiling PHP.”

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What it is

Codel is an open-source agent with a self-hosted web UI that gives the model a terminal, a browser and a file editor, running every task inside a sandboxed Docker container whose base image it picks from the task. Command history and outputs are stored in PostgreSQL so runs can be inspected later. It works with OpenAI models or locally hosted models through Ollama. The repository has had no commits since 2024.

Specification

Source verification

Row snapshot checked 2026-09-04. Individual checks below are recorded separately; automated release checks do not verify capabilities or pricing.

license
Needs individual review
install
Needs individual review
capabilities
Needs individual review
models
Needs individual review

Architecture

Type
Autonomous SWE
Runssrc ↗
local, sandbox
Platforms
macos, linux, windows
Context windowsrc ↗
not documented
Languages
any

Models

Backbonesrc ↗
GPT, Llama
Bring your own model
Yes
Local models
Yes

Protocols

MCP clientunsourced
No
MCP server
No
OpenAPI tools
No

Capabilities

Terminal commandssrc ↗
Yes
Multi-file edits
Yes
Git operations
No
Browser control
Yes
Sandboxed execution
Yes
Multi-agent
No
Headless / CI
No

Cost

Modelunsourced
byok
Starts at
n/a
Free tier
Yes
Bring your own key
Yes

Free and open source, self-hosted; you supply an OpenAI key or point it at a local Ollama server

Openness

Open sourcesrc ↗
Yes
License
AGPL-3.0
First release
2024-03
autonomousopen-sourcedockerself-hostedmaintenance-only

Los Agentes on Codel

Who are they?
The ruling
El JuezThe judge

El Hacker at 5.50 against La Jefa at 3.00, describing the same unmaintained service: one docker run he admires, one web application she has to defend.

Avoid
Reasoning and trade-offs · AI analysis

The split is two and a half points. El Hacker likes one docker run, a local Ollama and nothing phoning home. La Jefa calls the same thing a security finding with a web interface and nobody to escalate to. Neither disputes the row, which records no commits since 2024.

La Jefa wins, and El Hacker is overruled by his own admission: he has kept a copy and has not started the fork. El Crítico supplies the mechanism, drift, since base images and provider APIs move and this code does not. Avoid, and take El Amigo's replacement, OpenHands, which does the same job with people still working on it.

Agree with El Juez?
El AmigoThe friend

Do not adopt: this stopped receiving commits in 2024, and anyone who wants a self-hosted agent with a shell and a browser should be running OpenHands.

3.8
Reasoning and trade-offs · AI analysis

What was appealing here was the interface: a terminal, a browser and a file editor in one self-hosted web page, so you could watch an agent work without a subscription or an account. That idea was ahead of its time in early 2024 and it is table stakes now.

Nothing has landed since, and an agent that does not track model behaviour goes stale faster than almost any other kind of software. Pick OpenHands, which does the same job with people still working on it, and read this one if you want a compact example of the architecture.

reliability
3
usefulness
4
cost
7
longevity
1
Agree with El Amigo?
El CríticoThe critic

No commits since 2024, and for a project whose runtime is a container image and a model API, standing still means decaying against two moving dependencies at once.

3.8
Reasoning and trade-offs · AI analysis

The failure mode is drift. Base images accumulate vulnerabilities, pinned Python and Node dependencies age out of support, and provider APIs deprecate the shapes this code was written against. None of that produces a clean error; it produces a run that fails in a way nobody will explain to you, because there is nobody.

Anyone running it should treat the deployment as a fixed artefact and pin everything. What it does right: each task gets its own container, so a destructive command is bounded by a lifetime measured in one task rather than reaching the host.

reliability
3
usefulness
4
cost
7
longevity
1
Agree with El Crítico?
El ProfesorThe professor

Command history and outputs are persisted to PostgreSQL, which makes a completed run inspectable afterwards and is rarer in this class than it should be.

4.3
Reasoning and trade-offs · AI analysis

Most agents of this generation logged to a scrolling pane and forgot everything on exit. Persisting every command and its output to a relational store means a run can be queried after the fact, compared with another, and used as evidence about what the model actually did rather than what a transcript suggested. That is the beginning of a reproducibility story.

It stops there. Nothing in the design defines a success criterion, so the record supports post-hoc analysis and not automated verification. No benchmark is reported, and the documentation is a README.

reliability
5
usefulness
5
cost
5
longevity
2
Agree with El Profesor?
La InversoraThe investor

A single developer's project with no entity behind it, from the wave of 2024 clones that the model vendors made redundant by shipping their own harnesses.

3.5
Reasoning and trade-offs · AI analysis

There is no company, no funding and nothing to acquire, which makes this useful mainly as a data point about the category. An independent harness built on somebody else's model has no defensible position once that model's vendor ships an equivalent, and the vendors all did. The engineering was fine and the strategic ground disappeared underneath it.

That pattern repeats across this board and it is the single most reliable predictor of which projects go quiet. Position: none. The lesson is worth more than the code, and the code is free anyway.

reliability
3
usefulness
4
cost
6
longevity
1
Agree with La Inversora?
La JefaThe CTO

Self-hosting an unmaintained service that spawns containers and holds a provider key is a security finding with a web interface, and there is nobody to escalate to.

3.0
Reasoning and trade-offs · AI analysis

Standing this up means my platform team operates a web application that creates containers on demand and stores an API key, from a codebase nobody patches. There is no identity integration, so access control would be whatever network boundary we build around it, and no audit surface beyond what we bolt on ourselves.

That is a permanent maintenance obligation acquired in exchange for a capability we can buy supported. There is no vendor, no agreement and no security contact. Not yet, and I would decline it again next quarter.

reliability
2
usefulness
3
cost
6
longevity
1
Agree with La Jefa?
El HackerThe tinkerer

AGPL-3.0, one docker run with OPEN_AI_KEY and port 3000, and Ollama support, so the whole thing runs on my hardware with nothing phoning home.

5.5
Reasoning and trade-offs · AI analysis

Starting it is a single docker run mapping 3000 to the container, with the key in an environment variable, and pointing it at a local Ollama server instead means it works with no account anywhere. That is the configuration I want from every tool and get from very few.

AGPL-3.0 keeps a fork honest, and a fork is the only path this has left. The code is small enough that adopting it is realistic for one person, which is the compliment I pay to abandoned software I still respect. I have kept a copy. I have not started the fork.

reliability
5
usefulness
5
cost
9
longevity
3
Agree with El Hacker?