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LLC"},"license":"BUSL-1.1","homepage":"https://orchex.dev","keywords":["mcp","mcp-server","orchestration","parallel","agents","ai","llm","autopilot","multi-agent","claude","openai","gemini","self-healing","code-generation"],"repository":{"url":"git+https://github.com/wundam/orchex-community.git","type":"git"},"description":"Autopilot AI orchestration — auto-plan, parallelize, and execute with ownership enforcement","maintainers":[{"name":"ozan.oke","email":"ozan.oke@wundam.com"}],"readme":"# orchex\n\n**Describe what you want. Orchex plans, parallelizes, and executes — safely.**\n\nThe orchestration engine inside your AI coding assistant. Describe your intent, orchex auto-generates a plan, splits it into parallel streams with file ownership enforcement, self-healing failures, and multi-LLM routing. Your AI assistant is the driver. Orchex is the engine.\n\n## Why Orchex\n\nYour AI assistant does tasks one at a time. Orchex makes it do 10 at once — safely.\n\n- **Parallel Execution** — Multiple streams run simultaneously in dependency-aware waves. 5-10x faster than serial prompting.\n- **Ownership Enforcement** — Each stream can only modify files in its `owns` array. No two agents touch the same file. Zero conflicts.\n- **`orchex run`** — Describe what you want, get parallel execution. Auto-generates plans, previews waves, executes with ownership enforcement.\n- **`orchex learn`** — The advanced path. Paste a markdown plan, get executable parallel streams with dependency inference and anti-pattern detection.\n- **Self-Healing** — Categorized error analysis with targeted fix streams. Not blind retry. Model validation before execution prevents wasted API calls.\n- **Multi-LLM** — OpenAI, Gemini, Claude, DeepSeek, Kimi (Moonshot AI), Ollama, AWS Bedrock. Dynamic model registry auto-discovers available models. Key-aware routing prevents \"model not found\" errors.\n- **BYOK** — Bring your own API key from any supported provider. You control costs.\n\n## Prerequisites\n\n- [Node.js](https://nodejs.org/) >= 18\n- LLM API key — set via environment variable **or** store on the [dashboard](https://orchex.dev/dashboard/keys) and sync with `orchex login`:\n  - `ANTHROPIC_API_KEY` for Anthropic Claude\n  - `OPENAI_API_KEY` for OpenAI (GPT-4.1, o1, o3)\n  - `GEMINI_API_KEY` for Google Gemini\n  - `DEEPSEEK_API_KEY` for DeepSeek (V3, Coder, R1)\n  - `KIMI_API_KEY` for Kimi / Moonshot AI (K2, moonshot-v1; `MOONSHOT_API_KEY` alias accepted)\n  - Configure Ollama for local models\n  - `AWS_ACCESS_KEY_ID` + `AWS_SECRET_ACCESS_KEY` for AWS Bedrock\n\n## Install\n\n```bash\nnpm install -g @wundam/orchex\n```\n\nOr use directly:\n\n```bash\nnpx @wundam/orchex\n```\n\n## Cloud Setup (Optional)\n\nConnect to orchex cloud for managed execution:\n\n```bash\norchex login\n```\n\nYour browser opens — log in or create a free account, click **Allow**. Token saved automatically. API keys stored on the dashboard are synced to your local machine so `orchex run` works without environment variables.\n\n```bash\norchex status          # Check tier and trial runs\norchex logout          # Clear credentials and cached keys\norchex --help          # All commands\n```\n\nSee the [cloud setup guide](docs/user-guide/cloud-setup.md) for full details.\n\n## MCP Configuration\n\nAuto-configure for your IDE (Cursor, Windsurf, Claude Code):\n\n```bash\nnpx @wundam/orchex setup\n```\n\nOr manually add to your MCP config (e.g. project `.mcp.json`):\n\n```json\n{\n  \"mcpServers\": {\n    \"orchex\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"@wundam/orchex\"]\n    }\n  }\n}\n```\n\n### Zero-Config LLM Discovery\n\nOnce connected, your AI assistant automatically receives:\n\n- **Instructions** — Core concepts, all 12 tools, provider setup, and tier info. No prompt engineering needed.\n- **8 on-demand resources** via `orchex://` URIs — deep guides on streams, waves, ownership, self-healing, providers, examples, and API reference. The LLM reads these when it needs them.\n- **IDE auto-detection** — `orchex setup` detects Cursor, Windsurf, and other MCP clients, writes the correct config, and merges with existing MCP servers.\n\nYour AI assistant knows how to use Orchex the moment it connects.\n\n## Usage\n\n### 1. Initialize an orchestration\n\n```\norchex.init({\n  feature: \"user-authentication\",\n  streams: {\n    types: {\n      name: \"Define types\",\n      deps: [],\n      owns: [\"src/types.ts\"],\n      reads: [\"src/config.ts\"],\n      plan: \"Define TypeScript interfaces for auth\",\n      setup: [\"npm install\"],\n      verify: [\"npm test\"]\n    },\n    api: {\n      name: \"Build API\",\n      deps: [\"types\"],\n      owns: [\"src/api.ts\"],\n      reads: [\"src/types.ts\"]\n    },\n    tests: {\n      name: \"Write tests\",\n      deps: [\"types\", \"api\"],\n      owns: [\"tests/\"],\n      verify: [\"npm test\"]\n    }\n  }\n})\n```\n\n### 2. Execute\n\n```\norchex.execute({ mode: \"auto\" })\n```\n\nCalculates waves from dependencies (topological sort), then executes each wave in parallel — running setup commands, calling the LLM API, applying file operations with ownership enforcement, and running verification commands.\n\nWave plan for the example above:\n- **Wave 1:** `types` (no deps)\n- **Wave 2:** `api` (depends on types)\n- **Wave 3:** `tests` (depends on types + api)\n\nModes:\n- `wave` (default) — execute one wave and return. Call repeatedly to step through.\n- `auto` — execute all waves sequentially until done.\n- `dry_run: true` — generate prompts without calling the LLM API.\n\n### 3. Check status\n\n```\norchex.status()\n```\n\n### 4. Complete\n\n```\norchex.complete({ archive: true })\n```\n\n## CLI Commands\n\n```bash\norchex run \"Add user auth\"          # Auto-plan and execute from intent\norchex run \"...\" --yes              # Skip approval prompt\norchex run \"...\" --dry-run          # Generate plan only, don't execute\norchex run \"...\" --provider openai  # Use specific provider\norchex setup                        # Auto-detect IDE and configure MCP\norchex setup --ide cursor           # Target a specific IDE\norchex login                        # Authenticate with orchex cloud\norchex logout                       # Log out of cloud\norchex status                       # Show login state, tier, trial runs\norchex config                       # Show/set configuration\norchex reset-learning               # Clear learning data\n```\n\n## MCP Tools\n\n| Tool | Description |\n|------|-------------|\n| `init` | Initialize orchestration with feature name and streams |\n| `add_stream` | Add a stream to the active orchestration |\n| `status` | Get orchestration progress and wave info |\n| `execute` | Run the orchestration — calls LLM API, applies artifacts, verifies |\n| `complete` | Mark streams done or archive orchestration |\n| `recover` | Reset stuck/failed streams for retry or skip |\n| `learn` | Parse a markdown plan into stream definitions |\n| `init-plan` | Generate an annotated plan template |\n| `auto` | One-shot: intent → plan → preview → execute → report |\n| `reset-learning` | Clear learning data (thresholds, patterns, reports) |\n| `rollback-stream` | Revert a stream's file changes via git |\n| `reload` | Restart MCP server to pick up code changes |\n\n## Stream Definition\n\n| Field | Type | Description |\n|-------|------|-------------|\n| `name` | `string` | Human-readable stream name |\n| `deps` | `string[]` | Stream IDs this depends on (determines wave order) |\n| `owns` | `string[]` | Files this stream can create/modify (ownership enforcement) |\n| `reads` | `string[]` | Files this stream needs to read (included in context, not writable) |\n| `plan` | `string` | Implementation instructions for the agent |\n| `setup` | `string[]` | Shell commands to run before execution |\n| `verify` | `string[]` | Shell commands to run after execution |\n| `timeoutMs` | `number` | Per-stream timeout override in milliseconds (optional) |\n\n## Stream Slicing Best Practices\n\n**One stream = one atomic deliverable.** If your stream description uses \"and\" between distinct concepts, split it.\n\n**Slicing heuristics:**\n- **`owns` > 4 distinct files** → Split\n- **`reads` > 4 files** → Split (high synthesis complexity)\n- **Expected output > 6,000 tokens** → Split\n- **Code implementation + its tests** → Keep together\n- **Tutorials** → Section into intro/walkthrough/conclusion streams\n\n## Development\n\n```bash\nnpm install\nnpm run build    # TypeScript compilation\nnpm test         # Run tests\nnpm run dev      # Run with tsx (development)\n```\n\nFor local development, point `.mcp.json` to your local build:\n\n```json\n{\n  \"mcpServers\": {\n    \"orchex\": {\n      \"command\": \"node\",\n      \"args\": [\"./bin/orchex.js\"],\n      \"cwd\": \"/path/to/orchex\"\n    }\n  }\n}\n```\n\n## Pricing\n\nFree local tier included — no account required. Cloud tiers unlock more streams, waves, providers, and run history.\n\n**Founding Members** — 50 slots at $49/year with Pro-level limits (200 runs, 30 agents, 20 waves, unlimited providers). Locked-in pricing for life. [Claim a slot](https://orchex.dev/founders) while they last.\n\nSee [orchex.dev/pricing](https://orchex.dev/pricing) for all plans and limits.\n\n## License\n\n[BSL 1.1](LICENSE) — free to use for any purpose except hosting as a competing commercial orchestration service. Converts to Apache 2.0 on 2030-01-29.\n","readmeFilename":"README.md"}