Goose
Block's open-source (Apache-2.0) AI coding agent that runs locally, works with any LLM, and uses MCP to run commands, debug and build projects end-to-end. Free; you pay only for the model you connect.
Work at Goose? Manage this listing
Our take
Goose is Block's open-source coding agent that runs on your machine, plugs into any model, and does the work: running commands, debugging, and building features across files, not just suggesting code. It is MCP-native, so it can use external tools and act as a tool for other agents. Free under Apache-2.0; your only cost is the model API. Capable, though reliability tracks the model you give it.
Best for
Developers who want a free, self-hostable autonomous coding agent and dislike being locked to one model or vendor.
Pros
- Open-source (Apache-2.0); runs locally, no lock-in
- Works with any LLM you bring
- MCP-native: consumes and exposes tools
- Backed by Block, governed via the Linux Foundation
Cons
- CLI/desktop setup and a model key required
- Task reliability depends on your chosen model
- Less hand-holding than a polished commercial IDE
How it compares
Like Claude Code or Codex in ambition, but fully open and model-agnostic, closer to Cline in spirit, with first-class MCP support and foundation governance.
Full review
Goose is an open-source AI agent for software work, built by Block (the company behind Square and Cash App) and now governed under the Linux Foundation's Agentic AI Foundation. Unlike autocomplete tools, it runs commands, reads and edits across a codebase, fixes failing tests, and can scaffold a project from scratch, locally, with whichever model you point it at.
Its MCP support is first-class: Goose can consume MCP servers as tools and expose itself as one for other agents to call, which makes it a flexible building block in a larger setup. Because it is Apache-2.0 and model-agnostic, the cost question is simple for Indian developers: the agent is free, and you choose a model to match your budget, from a frontier API to a local model via Ollama. As with any coding agent its real outcome depends heavily on the model and how tightly you scope the task, so keep a review step on anything it ships.
Cloudkart Trust Graph
3.8/5- Actual Utility4/5
Source: Initial LLM-authored rubric (backfill)
- Ease of Use3/5
Source: Initial LLM-authored rubric (backfill)
- Pricing Fairness5/5
Source: Initial LLM-authored rubric (backfill)
- Reliability3/5
Source: Initial LLM-authored rubric (backfill)
- Differentiation4/5
Source: Initial LLM-authored rubric (backfill)
Scored as of . Each score is versioned and auditable; vendors cannot buy it.
How this score is set
- Editorial rubric
- Primary signal — five dimensions, 3.8/5 average.
- Community reviews
- None yet.
- Pricing verified
- Not yet verified
- Independence
- Score set by our editorial team before any affiliate relationship is considered. No vendor can buy it.
Frequently asked questions
- Is Goose free, and how much does it cost?
- Goose is open source and free to self-host.
- Who is Goose best for?
- Developers who want a free, self-hostable autonomous coding agent and dislike being locked to one model or vendor.
- How is Goose rated on Cloudkart.ai?
- Goose scores 3.8 out of 5 on the Cloudkart.ai rubric, which weighs actual utility, ease of use, pricing fairness, reliability and differentiation. Scores are set editorially and can never be bought.
Community reviews
No community reviews yet. Be the first to share how Goose works for you.
Relevant tools
More tools in AI Coding Assistants.
Composio
Composio provides the execution infrastructure that connects AI agents to real software. It sits at the tooling and connectivity layer of the agent stack, giving developers one framework - SDKs, a CLI and 850+ pre-built connectors - to let agents act across apps such as GitHub, Slack and Salesforce. It handles the hard parts: complex authentication and OAuth, plus remote sandboxed environments for safe execution, exposed over the Model Context Protocol so agents can reason and then reliably take action. The platform is built for production, with SOC 2 and ISO 27001:2022 certifications and deployment across public cloud, VPC and on-premises. Composio operates from San Francisco and Bangalore and raised a $25M Series A led by Lightspeed, with angels including Vercel's Guillermo Rauch and HubSpot's Dharmesh Shah.
LiteLLM
LiteLLM, from BerriAI, is an open-source AI gateway that gives you a single OpenAI-compatible interface to 140+ providers and 2,500+ models, including OpenAI, Anthropic, Gemini, Bedrock, Azure, Mistral, Ollama and vLLM. You can use it as a lightweight Python SDK for direct calls, or deploy the proxy server as a centralized gateway for a team, with virtual keys, budgets, load balancing, rate limiting, request logging and LLM guardrails. It has become a default building block in the AI stack, with 45,000+ GitHub stars, 240M+ Docker pulls and over a billion requests served, and is used by companies including Netflix, Adobe and Stripe. The core is free; an enterprise tier adds JWT auth, SSO/SAML, audit logs, SLAs and dedicated support.
Claude Code
Terminal-based agentic coding tool from Anthropic for autonomous multi-step coding tasks.
Kiro
AWS agentic IDE built around spec-driven development: it writes a spec, then builds matching code, tests and docs across IDE, CLI and web.
Compare Goose head-to-head: vs Composio · vs LiteLLM · vs Claude Code · vs Kiro