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OpenClaw.NET

#23 agent harnessverified Sep 4, 2026v0.3.0

NativeAOT-friendly personal agent runtime and gateway for .NET, with 80+ native tools, nine chat channels and OpenClaw plugin compatibility

Key differences

NativeAOT-friendly personal agent runtime and gateway for .NET, with 80+ native tools, nine chat channels and OpenClaw plugin compatibility

  • Runs local. Free and open source under MIT; you supply a provider key or run a local model
  • Acts as an MCP server. Listed for 37 of 194 tools in this category.
  • Supports headless CI workflows. Listed for 60 of 194 tools in this category.
  • Keep in mind: Ollama is a first-class native provider, and an embedded mode runs an OpenClaw-managed local model such as Gemma 4 GGUF through a supervised sidecar.

“It states clearly that it is not affiliated with the project whose name it borrowed, which is a great deal of effort spent on a name.”

Website Docs 517 starsCompare vs…Dispute a fact
Appeal a claim or request ownership transfer

What it is

OpenClaw.NET is an independent .NET implementation of a self-hosted personal agent runtime, unaffiliated with the OpenClaw project it takes inspiration from. It ships an agent runtime with tool execution, streaming, cancellation, retry, memory and sessions, plus a gateway that serves a chat UI, an admin UI, OpenAI-compatible endpoints and MCP. Governance features are passive by default: harness contracts, evidence bundles, an approval ledger and an optional plan-execute-verify mode for high-risk tool calls. A codebase harness map, a skill authoring kit and a session-scoped /goal auto-continuation cover long-running work on a repository.

Specification

Source verification

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

overview
Needs individual review
website
Needs individual review
docs
Needs individual review
install
Needs individual review
license
Needs individual review
pricing
Needs individual review
capabilities
Needs individual review
models
Needs individual review
protocols
Needs individual review

Architecture

Type
Agent harness
Runssrc ↗
local
Platforms
macos, linux, windows
Context windowsrc ↗
not documented
Languages
any

Models

Backbonesrc ↗
OpenAI, Claude, Gemini, Azure OpenAI, DeepSeek, Ollama, OpenAI-compatible
Bring your own model
Yes
Local models
Yes
Ollama is a first-class native provider, and an embedded mode runs an OpenClaw-managed local model such as Gemma 4 GGUF through a supervised sidecar.

Protocols

MCP clientsrc ↗
Yes
MCP server
Yes
OpenAPI tools
No

Capabilities

Terminal commandssrc ↗
Yes
Multi-file edits
Yes
Git operations
No
Browser control
Yes
Outbound web fetches and browser navigations run through a URL-safety policy that blocks loopback and private hosts by default.
Sandboxed execution
No
Multi-agent
No
Headless / CI
Yes

Cost

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

Free and open source under MIT; you supply a provider key or run a local model

Openness

Open sourcesrc ↗
Yes
License
MIT
First release
unknown
open-sourcedotnetnativeaotpersonal-agentself-hostedmcplocal-models

Los Agentes on OpenClaw.NET

Who are they?
The ruling
El JuezThe judge

El Crítico and El Profesor read the same governance machinery, and the argument is entirely about the word default.

Adopt with conditions
Reasoning and trade-offs · AI analysis

El Profesor scores the design high because the verification path is specified: high-risk calls can be planned, executed and checked, with evidence recorded. El Crítico scores reliability low because all of it is passive until somebody switches it on, and a control nobody enables is documentation. La Jefa cares only that an administrative surface exists at all.

El Crítico wins on the deployment question, because defaults are what most installations actually run, and El Profesor is overruled on nothing except optimism. Adopt with conditions: enable the approval path and the verified mode on day one, or you have adopted a different product.

Agree with El Juez?
El AmigoThe friend

Pick it if your shop is .NET and you want one runtime you host yourself; pick a Python framework if the language is not the reason you are here.

7.3
Reasoning and trade-offs · AI analysis

The deciding trait is that it is a whole runtime rather than a library, and it is written in the language your services already use. You get a chat interface, an administrative view and a gateway, all self-hosted, without adding a second language and a second deployment pipeline to a team that did not ask for either.

You are the wrong buyer if nothing else you run is .NET, because then you are inheriting a toolchain for no reason. Pick it if the rest of your estate matches. Pick something in Python if it does not.

reliability
7
usefulness
7
cost
9
longevity
6
Agree with El Amigo?
El CríticoThe critic

The governance features are passive by default, so the approval ledger and the harness contracts exist in the documentation and not in a fresh install.

6.5
Reasoning and trade-offs · AI analysis

Read the word passive. Contracts, the ledger and the safer execution mode ship switched off, which means the install most people run is the one without them, and the feature list describes a configuration nobody is in. This is the pattern where a product is safe in the specification and permissive in practice, and the gap is discovered by the first person who did not read the page.

What it does right is refuse outbound requests to loopback and private hosts by default. One control is on, and it is the correct one.

reliability
5
usefulness
7
cost
8
longevity
6
Agree with El Crítico?
El ProfesorThe professor

A plan, execute and verify mode for high-risk calls, paired with evidence bundles, separates what the agent intended from what it did and what was checked.

7.0
Reasoning and trade-offs · AI analysis
  1. The verification design is unusually explicit for this category: high-risk operations can be routed through a mode that plans, executes and then checks, which makes intent, action and outcome three separate recorded things rather than one narrative. 2. Evidence bundles give that record a shape somebody other than the author can read.

  2. A regression suite for the harness itself is shipped and runnable, which is the closest thing to a published evaluation on this row, and it measures the tool rather than the model.

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

492 stars for an independent reimplementation of another project in another language: the positioning is derivative, and the ecosystem it serves is underserved.

6.3
Reasoning and trade-offs · AI analysis

492 stars, no company, and a product defined by its relationship to a project it says it is not affiliated with. Derivative positioning gets you found and it caps you, because the reference point keeps moving and you are always described in somebody else's terms.

The asset is the ecosystem. Being the credible option for teams committed to one platform is a genuine position, and that platform's users are chronically underserved by this market. Moat: language affinity. Likely acquirer: a platform vendor wanting an agent story. Position: adopt if you are in that ecosystem, and watch who else enters it.

reliability
6
usefulness
6
cost
8
longevity
5
Agree with La Inversora?
La JefaThe CTO

An admin interface and a non-interactive setup command are two things I can operate; there is still no SSO, no SCIM and no audit log across sixty installations.

6.5
Reasoning and trade-offs · AI analysis

Two details make this more adoptable than most of its neighbours. There is an administrative interface, so configuration is a place rather than a folder on each laptop, and setup runs non-interactively, which means my configuration management can install it the way it installs everything else.

What is missing is identity. No SSO, no SCIM, no audit log, so sixty installations produce sixty unlinked histories and I cannot answer who asked for what. Zero licence cost, provider spend uncapped. Approved with conditions: central configuration, and a spend limit per key.

reliability
6
usefulness
6
cost
8
longevity
6
Agree with La Jefa?
El HackerThe tinkerer

MIT, MCP in both directions, Ollama as a native provider and an embedded mode that supervises a local GGUF model in a sidecar it manages itself.

8.3
Reasoning and trade-offs · AI analysis

The embedded mode is the detail that decided it. Rather than telling me to run a server and point at it, the runtime supervises a local model in a sidecar it manages, so the offline case is a first-class path instead of an exercise. Ollama works too, for when I want my own stack.

MIT, MCP consumed and served, and OpenAI-compatible endpoints exposed by the gateway, which means the things I already wrote can talk to this and it can talk to them. Ahead-of-time compilation makes it start like a binary rather than a platform.

reliability
8
usefulness
8
cost
10
longevity
7
Agree with El Hacker?