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Mon 07 Sept 19:30 UTC
LLM Toolsevaluationupdated 07 Sept 2026

agentdock review

AgentDock is an MCP runtime that lets an AI client operate files, shells, Git repositories, browsers, and long-running tasks on machines you control. It supplies the connection and permission layer between clients such as ChatGPT, Claude, or Codex and local computers, servers, or containers; it does not supply a chat interface or model inference.

Verdict

Our AgentDock run built in 31 seconds and passed all 82 tests, so the checked-out runtime is a credible candidate for an isolated, least-privilege host. Use it when one trusted AI client genuinely needs to work across several machines and you can narrow each service account or container. Skip it if you want the tool itself to contain a compromised or mistaken agent, because its own security model places that job on operating-system permissions and mounts.

We ran it

Lab card: what happened when we ran agentdockScreenshot of agentdock (uvwt.github.io/agentdock-docs)
Install✓ · 33s78 packages
Build✓ · 31s
Tests✓ · 60s82 passed · 0 failed of 82 (go test)
Repo639 files~92,099 lines of source · 5.5 MB · 4 CI workflows · Dockerfile

Answers from our run

Does agentdock build from source?

Dependencies installed in 33 seconds (78 packages), and the build succeeded in 31 seconds. We cloned commit 84abde2 into a clean Debian container with 3 CPUs and no project-specific setup.

Do agentdock's tests pass?

Yes: 82 of 82 passed when we ran the project's own test command (go test). Some failures need services or credentials a bare container does not have.

Who should not use agentdock?

Anyone looking for a security sandbox by default: the project's security guide says the runtime inherits the operating-system user or container's permissions.

What are the alternatives to agentdock?

MCP Servers, Daytona, OpenHands. Our AgentDock run built in 31 seconds and passed all 82 tests, so the checked-out runtime is a credible candidate for an isolated, least-privilege host.

Setup4/5All 82 tests passed; remote OAuth and tunnels take extra work
Docs5/5Detailed English guides cover platforms, auth, tools, and limits
Community4/5671 stars, same-day pushes, and quick issue follow-up
Maturity3/5v0.8.2 is well tested, with Windows and fallback fixes still open

Who it’s for

Developers who want one AI conversation to work across a laptop, server, and container.
Self-hosters prepared to run the service as a restricted user and expose only chosen directories.
MCP users who need file, shell, Git, browser, Skill, and dynamic-server tools from one runtime.
Operators who can manage HTTPS, OAuth or Bearer Tokens, and Cloudflare Tunnel when remote access is required.

Who it’s NOT for

Anyone looking for a security sandbox by default: the project's security guide says the runtime inherits the operating-system user or container's permissions.
Teams unwilling to let an AI client execute commands or modify real files: those actions are the product's central purpose, and ~/AgentDock is not a strong boundary.
Web ChatGPT users who cannot publish an authenticated HTTPS endpoint: the official guide requires public HTTPS and OAuth, with several proxy routes forwarded.
Windows fleets where an antivirus alert blocks deployment: open issue 41 reports Defender quarantining the v0.8.0 x64 binary, and the report remains open.
Windows users who cannot tolerate background console flashes: issue 52 reports them during exec_command calls on v0.8.1.
Buyers expecting a built-in AI assistant: AgentDock explicitly provides neither a chat interface nor model inference.

Setup reality

Our sandbox install succeeded in 33 seconds and installed 78 packages. The build passed in 31 seconds. Tests also passed: all 82 completed successfully in 60 seconds. The 5.5 MB checkout contained 639 files and roughly 92,099 lines of source.

Local MCP use needs a client plus the URL on port 8765 and, for Docker, a Bearer Token. Web ChatGPT needs a public HTTPS address, OAuth password, persistent token secret, and proxy or Cloudflare Tunnel configuration. Browser control needs a supported browser; ACP needs a separate coding-agent adapter and any provider credentials it uses.

AgentDock defaults to loopback, but its working directory is not a security barrier. Native installs inherit the runtime user's access, while Docker depends on mounted volumes. Desktop automation is unavailable from Docker, and the security guide recommends a dedicated low-privilege user for server deployments.

One MCP endpoint can operate several machines

AgentDock's default MCP endpoint is http://127.0.0.1:8765/mcp, and each instance controls the machine where it runs. The service exposes file, command, Git, browser, Skill, task, and dynamic MCP operations through Streamable HTTP. Adding instances lets one conversation reach a laptop, LAN host, or cloud server. AgentDock supplies execution and structured results; ChatGPT, Claude, Codex, or another compatible client supplies the model and conversation.

The breadth is useful when work crosses device boundaries. A request can inspect a process on a server, edit a repository on a workstation, or drive a browser with saved login state. Recoverable tasks keep goals and checkpoints for longer jobs. State lives under ~/.agentdock, while relative file and command operations start in ~/AgentDock. Those 2 paths organize the runtime, but neither replaces operating-system access controls.

The operating-system user is the security boundary

The security guide names 3 practical boundaries: runtime-user permissions, container mounts, and network policy. It says AgentDock is not a complete operating-system sandbox. A native service can reach whatever its runtime user can reach, while a Docker service is limited by its container user and mounted volumes. The recommended server pattern is a dedicated low-privilege account with access only to required project directories. Command execution and file modification are deliberate capabilities, so chat instructions cannot replace those host controls.

Network defaults are more conservative. The service listens on 127.0.0.1:8765, and a non-loopback address refuses to start unless Bearer Token or OAuth authentication is configured. OAuth requires a password of at least 12 characters and a persistent signing secret of at least 32 bytes. Public endpoints must use HTTPS. Those checks reduce accidental exposure, while the operator still decides who can authenticate and what the runtime account can do afterward.

What happened when we ran it

Our sandbox installed 78 packages in 33 seconds. Building commit 84abde2 succeeded in 31 seconds, and all 82 tests passed in 60 seconds. The repository occupied 5.5 MB before dependencies and contained 639 files with roughly 92,099 lines of source. Among these three assigned projects, AgentDock was the only available repository whose complete measured test step passed.

The checkout had 4 CI workflow files, a Dockerfile, and a Compose file. There was no top-level tests directory, which does not imply missing tests in a Go project because package tests usually live beside their source. The passing run is useful evidence about the checked-out commit under 3 CPUs and 8 GB of RAM. It does not show that a shell command chosen by an agent is safe or that a mounted home directory is appropriately restricted.

Web ChatGPT needs public HTTPS and OAuth

AgentDock's ChatGPT guide requires 3 things: a public HTTPS origin, OAuth, and an MCP URL ending in /mcp. Web ChatGPT cannot reach the local endpoint on port 8765. A temporary Cloudflare address works for a trial but can change after restart. A fixed address needs a Cloudflare-managed domain and Tunnel Token. Local clients can avoid that public setup and connect directly, with a Bearer Token when the deployment requires one.

Manual deployments must forward /mcp, /register, /oauth/*, and /.well-known/* through the reverse proxy. OAuth also needs the public server URL, a login password, and a token-signing secret that survives restarts. Closed issue 77 records one ChatGPT Plus user whose plugin appeared enabled but was not visible through the expected menus; the user later confirmed that asking ChatGPT directly to call AgentDock worked. That issue is useful troubleshooting evidence, not a permanent promise about every ChatGPT plan.

Browser and ACP features widen host access

Browser automation is disabled by default and can use Chrome, Chromium, or Edge after an operator enables it. Persistent profiles can retain logins, so the security guide recommends a dedicated browser profile. Docker cannot control the macOS desktop, and native desktop automation needs operating-system permissions. A browser session with cookies plus command access is a powerful combination; keep it away from a daily personal profile.

ACP is also disabled by default. Once enabled, it can start local coding-agent sessions and handle permission prompts. The configuration reference explicitly says ACP working directories have no AgentDock project-root allowlist and may use any directory accessible to the host process or container. Open issue 52 reports flashing console windows on Windows 11 during some v0.8.1 command calls. Open issue 41 reports Defender quarantining the v0.8.0 x64 binary, so Windows teams should test the current signed or unsigned artifact under their own endpoint policy.

v0.8.2 is active, with 2 fixes still awaiting merge

Release v0.8.2 shipped on September 4, 2026. It added a built-in user-guide Skill, expanded ACP adapter configuration, fixed OAuth metadata handling, and changed host environment forwarding to an explicit mapping. The release also added 10 MiB x 5 log rotation for several background-service paths. Release files have SHA-256 checksum companions, and the release workflow pulls and starts the published container image.

The last push was September 7, 2026, the day we fetched the repository. GitHub showed 671 stars and 4 open issues and pull requests: 2 issues and 2 pull requests. Pull request 67 proposes resource caps for fallback text search when ripgrep is absent. Pull request 68 would expose health details for dynamic MCP servers but says it is blocked on a protocol change. The activity is current and responsive; those open changes also show that resource limits and capability status are still being tightened.

Alternatives

ProjectWhat it isPick it when
MCP Servers gh↗Reference MCP servers that connect AI clients to specific tools and data sources.pick this instead when a few narrow integrations are enough and whole-machine command access would be excessive.
Daytona gh↗Infrastructure for creating isolated development environments for AI-written code.pick this instead when disposable workspaces and isolation matter more than operating an existing personal machine.
OpenHands gh↗A software-development agent with its own interface and runtime integrations.pick this instead when you want the coding agent itself, not an MCP bridge for a client you already use.

What people are saying

  1. [github-trending] uvwt/agentdock

Sources

  1. AgentDock repository and README
  2. AgentDock security model
  3. AgentDock configuration reference
  4. Connect ChatGPT to AgentDock
  5. AgentDock v0.8.2 release
  6. Issue 41: Windows Defender quarantine report
  7. Issue 52: Windows console window report
  8. Pull request 67: bounded fallback text search

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