Compare/Goose vs Windmill

AI tool comparison

Goose vs Windmill

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

G

AI Agents

Goose

Block's local-first AI agent with native MCP support, runs on your machine

Ship

75%

Panel ship

Community

Paid

Entry

Goose is Block's open-source local-first AI agent, built with native Model Context Protocol (MCP) support from the ground up. Unlike cloud-based agent platforms, Goose runs entirely on the developer's machine — connecting to local MCP servers, reading files, running shell commands, and integrating with local services without sending data to third-party infrastructure. The agent supports multiple LLM backends (Anthropic, OpenAI, local Ollama models) and exposes a plugin-style architecture where capabilities are added as MCP servers. This means any developer can extend Goose with custom tools — a database connector, a local calendar integration, a custom code execution environment — without modifying the core agent. The design reflects Block's privacy-first engineering culture. Goose has been growing steadily in the developer community, particularly among engineers at companies with strict data security requirements who want agent capabilities without cloud data exposure. The local-first + MCP-native combination is genuinely differentiated — most agent platforms either require cloud APIs or bolt MCP on as an afterthought rather than building around it.

W

Automation

Windmill

Open-source developer platform for scripts and workflows

Ship

100%

Panel ship

Community

Free

Entry

Windmill turns scripts into workflows, UIs, and scheduled jobs. Write in TypeScript, Python, Go, or SQL and get auto-generated UIs with approval flows.

Decision
Goose
Windmill
Panel verdict
Ship · 3 ship / 1 skip
Ship · 3 ship / 0 skip
Community
No community votes yet
No community votes yet
Pricing
Open Source (Apache 2.0)
Free (OSS), Pro $10/user/mo
Best for
Block's local-first AI agent with native MCP support, runs on your machine
Open-source developer platform for scripts and workflows
Category
AI Agents
Automation

Reviewer scorecard

Builder
80/100 · ship

The MCP-native architecture is the right bet for 2026. Instead of each agent building its own tool integration layer, the ecosystem converges on MCP servers as the universal extension mechanism. Goose being built around this from day one means it ages better than competitors who bolted MCP on later.

80/100 · ship

Scripts become workflows with auto-generated UIs. The approval flows and scheduling turn scripts into proper automation.

Skeptic
45/100 · skip

Running locally is a privacy win but also means you're responsible for setup, updates, and debugging when things break. For teams without a dedicated platform engineer, the operational overhead of a local-first agent is real. Also, Goose's cloud connectivity features (for collaboration) create the same privacy exposure it's trying to avoid.

80/100 · ship

Open-source Retool + n8n hybrid. The auto-generated UI from script parameters is surprisingly useful.

Futurist
80/100 · ship

Block building a local-first agent is a quiet but important data point: large companies are hedging against cloud AI dependency. As MCP becomes the standard protocol for AI tool connectivity, agents that natively speak MCP will have massive ecosystem advantages over those that need adapters.

80/100 · ship

Internal tooling from scripts with auto-generated UIs is the right abstraction for developer-built automation.

Creator
80/100 · ship

For creators who work with sensitive client material — brand assets, unreleased campaigns, personal client data — the local-first guarantee removes the biggest barrier to using AI agents professionally. I can let Goose read my project files without wondering if they'll appear in someone's training data.

No panel take

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