AI tool comparison
Goose vs Goose v1.29
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
AI Agents
Goose
Block's local-first AI agent with native MCP support, runs on your machine
75%
Panel ship
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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.
AI Agents
Goose v1.29
The open-source AI agent that uses your Claude, Gemini, or ChatGPT subscription
25%
Panel ship
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Community
Free
Entry
Block's open-source on-machine AI agent just hit v1.29, introducing Gemini ACP (Agent Client Protocol) support so you can run the full Goose agent stack using your existing Google subscription — no separate API key needed. It also added orchestration for sub-agents, adversarial agent mode to prevent information leaks, delegate sub-agent log display, and macOS sandboxing. With 35k+ GitHub stars and Rust-based architecture, Goose goes far beyond autocomplete: it builds projects, writes and executes code, manages files, and calls external APIs autonomously. The ACP approach means your Goose extensions are passed directly to Gemini, deepening the connection compared to plain CLI usage.
Reviewer scorecard
“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.”
“This is exactly the architecture I want: a local agent that doesn't lock me into one AI provider's billing. The Gemini ACP integration means my Google One subscription now funds actual dev automation. The adversarial agent mode is also clever — finally an agent that polices itself before it nukes your filesystem.”
“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.”
“Multi-agent orchestration sounds great until you're debugging a cascade failure at 2am wondering which sub-agent hallucinated first. The 35k stars are real but so is the complexity overhead. Claude Code and Cursor 3 have more polish for day-to-day use — Goose still feels like a power-user project.”
“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.”
“The ACP subscription model is the thin edge of a wedge that eventually makes AI provider lock-in irrelevant. When agents can switch between Claude, Gemini, and GPT seamlessly based on cost and availability, the moat moves to the orchestration layer. Block is quietly building that layer in the open.”
“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.”
“The MCP Apps and rich UI stuff is interesting for creative workflows, but Goose is fundamentally a developer tool. The learning curve before it does anything useful for non-devs is steep. I'll check back when the Neighborhood Extension for ordering food is the least niche thing it can do.”
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