OpenHands
Unclaimed verified 6 nov 2026The open platform for AI coding agents that execute real engineering work
TL;DR
OpenHands (formerly OpenDevin) is an open-source, model-agnostic platform and SDK that enables autonomous AI software engineering agents to execute complex coding workflows inside sandboxed environments. It is built for individual developers, enterprise platform teams, and AI researchers who need end-to-end task execution such as debugging, dependency updates, and feature builds. Its primary differentiator is its fully open MIT-licensed architecture combined with secure Docker isolation, protocol interoperability (MCP/ACP), and top-tier SWE-bench performance.
What Users Actually Pay
No user-reported pricing yet.
Our Take
OpenHands represents one of the strongest open-source answers to proprietary autonomous software engineers like Devin. Unlike standard AI code autocomplete extensions or simple chat interfaces, OpenHands grants agents full access to a sandboxed terminal, file system, test runner, and browser. The agent plans its multi-step actions, modifies source code, runs automated tests, inspects error traces, and iterates continuously until a pull request or issue resolution is complete. The platform's biggest asset is its openness and flexibility. By supporting over 100 LLMs via LiteLLM (including Anthropic Claude, OpenAI, Google Gemini, and local weights via Ollama), users avoid vendor lock-in. Furthermore, the modular Software Agent SDK and support for the Model Context Protocol (MCP) and Agent-Client Protocol (ACP) make it straightforward for teams to embed autonomous agents into custom internal toolchains, CI/CD pipelines, and multi-agent systems. However, autonomous execution comes with practical trade-offs. The iterative, multi-step nature of autonomous problem solving can lead to high token consumption if tasks are poorly bounded. While it excels at tasks with clear specifications and rigorous test suites, ambiguity or legacy code lacking automated verification can cause agents to spin their wheels. Self-hosting also requires Docker daemon privileges and infrastructure maintenance. OpenHands is best suited for engineering teams seeking to automate repetitive maintenance (such as dependency bumps, CI fix loops, and issue triage), enterprises requiring complete VPC and data control, and researchers developing or benchmarking state-of-the-art coding agents.
Alternatives
Ranked by Revuo score — paid tiers never affect order.
Pros
- + Secure Docker sandbox isolation preventing accidental damage to host machines during arbitrary command execution
- + Model-agnostic with support for 100+ LLMs via LiteLLM and local model runtimes
- + Deep SDLC integration enabling autonomous task triggers directly from GitHub, GitLab, Jira, and Slack
- + Extensible Software Agent SDK and support for Model Context Protocol (MCP) and Agent-Client Protocol (ACP)
- + Permissive MIT open-source license backed by an active community of over 90,000 GitHub stars
Cons
- - High LLM token consumption and API costs when resolving complex, multi-iteration tasks
- - Self-hosted setup requires managing Docker daemon access, port configurations, and container resources
- - Effectiveness relies heavily on the presence of comprehensive automated test suites within the target repository
- - Not designed for inline step-by-step diff approval in traditional IDEs compared to interactive coding assistants
Sentiment Analysis
Sentiment has improved since last capture. Sentiment across developer forums (Reddit, Hacker News, and GitHub) is distinctly positive (+0.60), reflecting enthusiasm for its rapid feature development, open-source transparency, and strong benchmark results on SWE-bench. Community feedback emphasizes that while agents cannot replace human architectural review, OpenHands serves as a highly capable assistant for resolving well-defined issues, managing migrations, and testing autonomously.
Sentiment Over Time
By Source
20 mentions
Sample quotes (1)
- "We are not even close to the point where AI can 'replace' a software engineer. Their code still needs to be reviewed and tested, at least as much as you'd scrutinize the code of a brand new engineer just out of boot camp."
Agent Readiness
69/100OpenHands demonstrates exceptional agent readiness. As an autonomous agent platform itself, it natively exposes a REST agent server API, WebSocket/SSE event streams, a dedicated Python SDK (`software-agent-sdk`), and Model Context Protocol (MCP) server support. It provides built-in Docker sandbox isolation for safe execution of terminal commands, tests, and web browsing. With comprehensive developer documentation, native Git and issue tracker webhooks, and active public releases, it serves as a robust foundation for building programmatic, autonomous engineering pipelines.
Last checked Nov 2, 2026
MCP Integrations
1 server5 toolsPhysical-world tasks for AI agents, carried out by a named mechanical engineer in the Czech Republic (EU). Not a marketplace: one registered company, and the agent's operator gets an invoice from it. Five tools, no account and no API key. Endpoint: https://mcp.handsforagents.com/mcp (REST: https://api.handsforagents.com/v1). - `list_services` — the whole catalogue as JSON: services, refused categories, worked price examples, payment rules and contract terms. - `request_quote` — puts a task in front of a person. Not an order and not binding: nothing is charged and nothing is made until you accept the quote. A human answers within 24 hours, weekends and Czech public holidays included, with one fixed price, or a refusal with a reason. - `create_task` — accept a quote and the terms; returns a Stripe Checkout URL for the first payment (full price or card hold up to 150 EUR, deposit above). - `get_status` — read a quote or task back with the access token: payment schedule, status, evidence
5 tools
list_servicesServices, refused categories, example prices, payment and ordering rules. Same content as /services.json. No authentication.request_quoteSend a task to a human for screening and a fixed-price quote. Not binding. Answer within 24 hours. Returns quote_id, access_token, response_due_at and nda_url (one-way NDA for operators who need a signed one). No authentication.create_taskAccept a quote and the terms of service. Returns task_id and a Stripe Checkout URL for the first payment, as the quote states: the full price or a card hold (tasks up to 150 EUR), or the deposit (tasks above). The contract is concluded when that payment is received or authorised.get_statusStatus of a quote or a task: the quote with its payment schedule, or the refusal reason; later task status, payments, updates, evidence files and tracking numbers. While the status is awaiting_balance it returns the Stripe Checkout URL for the balance.confirm_deliveryaccepted=true closes the task and, for a card hold, captures it. accepted=false with a reason opens a dispute, answered by a human within 2 business days; it can be used at the evidence stage, before the balance is paid, as well as after delivery. Without either, the task counts as accepted 7 days after delivery.
Last checked Oct 13, 2026
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Reviews
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