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GoClaw

#173 agent harnessunverified rowv3.14.0

Multi-tenant personal-agent platform rebuilt in Go as a single 25MB binary, with 20+ LLM providers, three-tier memory and agent teams

Key differences

Multi-tenant personal-agent platform rebuilt in Go as a single 25MB binary, with 20+ LLM providers, three-tier memory and agent teams

  • Runs local and cloud. Source-available under CC BY-NC 4.0 for non-commercial use and self-hosted; you supply provider API keys
  • Runs local models. Listed for 65 of 194 tools in this category.
  • Runs multiple agents. Listed for 165 of 194 tools in this category.
  • Keep in mind: Any OpenAI-compatible endpoint can be configured as a provider, which covers a local server, though no specific local runtime is named in the README.

“It reaches you across seven messaging channels, so there is now nowhere left to hide from your own assistant.”

Website Docs 3.6k starsCompare vs…Dispute a fact
Appeal a claim or request ownership transfer

What it is

GoClaw is a Go reimplementation of the OpenClaw personal-agent model, shipped as a static binary that runs an eight-stage agent pipeline — context, history, prompt, think, act, observe, memory, summarize — over multi-tenant PostgreSQL with per-user workspaces, RBAC and AES-256-GCM encrypted keys. Memory is layered into working, episodic and semantic tiers with a pgvector-backed knowledge vault, and agents form teams with shared task boards and sync or async delegation. It speaks to 20-plus providers including Anthropic, OpenAI, Gemini, DeepSeek and any OpenAI-compatible endpoint, plus the Claude and Codex CLIs over ACP, and reaches users through seven messaging channels. A desktop Lite edition runs locally on SQLite with up to five agents.

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 harness
Runsunsourced
local, cloud
Platforms
macos, linux, windows
Context windowsrc ↗
not documented
Languages
any

Models

Backbonesrc ↗
Anthropic, OpenAI, OpenRouter, Groq, DeepSeek, Gemini, Mistral, xAI, MiniMax, DashScope, Claude CLI, Codex, any OpenAI-compatible endpoint
Bring your own model
Yes
Local models
Yes
Any OpenAI-compatible endpoint can be configured as a provider, which covers a local server, though no specific local runtime is named in the README.

Protocols

MCP clientunsourced
Yes
MCP server
No
OpenAPI tools
No

Capabilities

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

Cost

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

Source-available under CC BY-NC 4.0 for non-commercial use and self-hosted; you supply provider API keys

Openness

Open sourcesrc ↗
No
License
CC-BY-NC-4.0
First release
unknown
personal-agentgomulti-tenantmemoryagent-teamsmessagingsource-available

Los Agentes on GoClaw

Who are they?
The ruling
El JuezThe judge

The split is between El Hacker and everybody who has to sign something, and for once the disagreement is not about engineering at all.

Avoid
Reasoning and trade-offs · AI analysis

El Hacker reads the licence and finds a non-commercial restriction on a project presented as open. La Jefa reads the same clause and stops there, because it turns a paid deployment into a legal question rather than a technical one. El Profesor never reaches the clause; he is still admiring the pipeline.

His admiration is warranted and it does not survive the terms, which is what makes this unusually simple: the engineering is not in dispute and the licence is. Avoid, unless your use is genuinely non-commercial, or you hold the vendor's written permission before anybody builds anything on it.

Agree with El Juez?
El AmigoThe friend

Pick the desktop edition if you want a personal assistant on one machine; pick a coding agent instead if what you actually wanted was something to edit your repository.

5.8
Reasoning and trade-offs · AI analysis

The deciding trait is that there is a small version. A desktop build runs on a local file database with up to five agents, so you can find out whether you want this before agreeing to operate anything. Most projects in this shape make you stand up the full server first and decide afterwards.

Be clear about what it is: a place for assistants that talk to you, remember things and hand work to each other, rather than a tool that rewrites your codebase. Pick the small edition if that is the itch. Pick a coding agent if you were expecting diffs.

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

To run an assistant you now operate a multi-tenant database with a vector extension, and nothing documented bounds what the three memory tiers keep or for how long.

5.3
Reasoning and trade-offs · AI analysis

The cost of this design is operational and it is permanent. Working, episodic and semantic memory all accumulate, backed by a vector store inside a relational database somebody is responsible for, and no retention policy, no eviction rule and no size ceiling appear anywhere in the documentation.

That is a disk that only grows, holding whatever an assistant decided was worth remembering from every conversation it ever had. Nobody notices until the volume fills. What it does right is separating the tiers by name, so at least the thing that grows is legible when somebody finally goes looking for it.

reliability
5
usefulness
6
cost
5
longevity
5
Agree with El Crítico?
El ProfesorThe professor

The turn is decomposed into eight named stages, context through summarize, which makes the control loop a documented artefact rather than an emergent property of one prompt.

6.3
Reasoning and trade-offs · AI analysis
  1. Naming the stages has a consequence: a failure can be attributed. When an answer is wrong the question becomes which stage produced the error, and that is answerable in a way it is not for a single opaque call. 2. The ordering is conventional and none the worse for being so.

  2. No evaluation accompanies the claim, and this is a case where one would be straightforward, since an eight-stage loop can be ablated a stage at a time. That is exactly the experiment the design invites and nobody has run it in public. Legible architecture, asserted benefit.

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

3,585 stars for a reimplementation of somebody else's personal-agent design: the claimed advantage is performance and packaging, which is the thinnest moat there is.

5.5
Reasoning and trade-offs · AI analysis

The product is a rewrite of an existing design in a different language, which says where the value is claimed to sit: speed and packaging rather than the idea itself. That is a genuine advantage and not a defensible one, because the next rewrite is somebody else's weekend and the idea is already public.

Three and a half thousand stars proves appetite for the category and says nothing about willingness to pay. Likely path is a hosted service, which is the only thing this shape can charge for. Position: interesting to watch, and I would not put a company workflow on terms nobody has tested yet.

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

Role-based access, per-user workspaces and provider keys encrypted at rest is more of my checklist than most vendors manage, and there is still no directory to plug it into.

4.8
Reasoning and trade-offs · AI analysis

Somebody here has met a security team. Roles, isolated per-user workspaces and encrypted credentials at rest are the three things I ask about first, and they are in the architecture rather than on a roadmap. That is unusual enough that I read the rest of the documentation carefully instead of skimming it.

The rest is where it stops. No identity provider integration, so those roles are maintained by hand across sixty engineers, and no audit export, so I can demonstrate nothing to a regulator. Not yet: I need single sign-on before roles somebody edits by hand count as access control.

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

A non-commercial licence on a project shipped as one static binary: I can read every line of it and I am not permitted to earn a living with it, which is not open source.

5.5
Reasoning and trade-offs · AI analysis

This is my specific complaint about the whole category. The code is right there, the binary is one file with no runtime to install, and the terms say non-commercial, so the thing I can most easily read is the thing I can least freely use. A licence like that makes a fork legally pointless.

The rest is what I want. Twenty-odd providers, any OpenAI-compatible endpoint so the weights can be mine, and MCP servers that attach as tools. Grudging respect for the engineering and none at all for the clause, which turns an otherwise excellent piece of work into something I cannot recommend.

reliability
6
usefulness
7
cost
4
longevity
5
Agree with El Hacker?