https://github.com/user-attachments/assets/d7f3d520-e39f-45cd-a525-77e5e8d00a75
Use from a coding agent
The local MCP endpoint exposes task submission, progress, messaging and cancellation to compatible coding agents. Genesis runs the development work with its own configured models; the caller supplies context and checks the returned changes. Build this revision from source and follow the guide to configure a local credential and connect your MCP host.
See development unfold
- Set an objective. Start a new project or bring an existing repository. Describe the outcome and constraints; Genesis decomposes the work as needed.
- Follow the work. Watch the recursive agent tree, inspect tasks and model usage, and review diffs in the desktop dashboard.
- Keep developing. Continue from accepted results, refine the objective, or move execution to a server while keeping your local dashboard.
New projects · Existing repositories · Remote development
Built with Genesis
Selected software worlds developed with Genesis.
| Project | What emerged | Reported result |
|---|
| C Compiler | A Rust-based C compiler built from scratch | 220 / 220 c-testsuite |
| MESA | 13 Fortran modules redeveloped in Rust | 1,052 / 1,052 (0 failures) Rust test suite |
| tbench-wasm | A software WebGL renderer in TypeScript | 2,017 / 2,019 (99.90%) Khronos WebGL CTS |
Latest evidence: EvoX Compiler · 2026-10-28
Explore all evidence →
The world persists. Agents do not.
An objective becomes local work. Managers break down the goal, delegate tasks, and review the results. Executors implement and validate candidate changes in isolated Git worktrees.
Each task has a place. An accepted software version records what has been built; a repository path defines context, responsibility, and scope. CONTEXT.md files make these local contracts explicit.
Accepted results carry forward. The hierarchy unfolds as development proceeds. Agents finish their episodes; software versions and project history remain as the starting point for subsequent work.
Explore the architecture →
Start with an objective
Desktop app
Download Genesis → for macOS, Linux, or Windows. The website selects the installer for your platform; all published builds are available in GitHub Releases.
- Install and open Genesis.
- Configure a provider profile in Settings (API key or supported subscription OAuth), then choose its default model and, where supported, reasoning effort.
- Create a project or select an existing repository, then describe what you want to build.
For example:
Add rate limiting to this API. Preserve existing endpoint behavior, make the limits configurable, and add tests for requests above and below the limit.
Installation guide · Model configuration
Want to understand or operate Genesis? Open Assistant (/assistant) — Genesis Assistant understands the running system and can act on it: it reads Genesis source and inspects runtime state without approval, drives tasks and scheduler/configuration changes only after you approve the exact action, and answers in your language. See the Genesis Assistant guide for capabilities and safety boundaries.
Headless server
Run the dashboard and agent runtime on Linux (x86_64 or ARM64) or macOS (Apple Silicon):
curl -LsSf https://genesis.evox.group/dl/install.sh | sh
genesis start
genesis status
genesis update --check # is a newer server release available?
genesis update # install it and restart the server
Open http://127.0.0.1:9999 and configure your model provider in Settings. The server listens on localhost by default and has no built-in authentication; use an SSH tunnel for remote access.
Server installation and service management →
Provider profiles and model selection
A provider profile represents an account: its models share authentication, endpoint, concurrency, peak-hour schedules, and rate-limit backoff. Separate account IDs keep separate resource pools, even when they use the same provider and model.
In the task form, select Provider profile → Model → Reasoning effort; reasoning is a model-specific slider shown only when supported. An explicit choice locks that concrete selection for the task and its agents. Auto (by rules) leaves selection to your configured rules and defaults.
For example, in ~/.config/genesis/config.toml:
[llm]
default_provider_profile = "openai-main"
[[llm.providers]]
id = "openai-main"
provider = "openai"
auth_mode = "api_key"
api_key_env_var = "OPENAI_API_KEY"
concurrency = 3
default_model = "gpt-5"
reasoning_efforts = ["low", "medium", "high"]
default_reasoning_effort = "medium"
context_window = 200000
# Optional schedule shared by all models in this account:
peak_concurrency = 1
peak_hours = [{ start = "09:00", end = "18:00", days = ["weekdays"] }]
off_peak_days = ["sat", "sun"]
timezone = "Asia/Hong_Kong"
[[llm.providers.models]]
model = "gpt-5"
[[llm.providers.models]]
model = "gpt-5-mini"
default_reasoning_effort = "low"
context_window = 128000
This is the beginning of the README. Read the rest at the original. Read the full README ↗
