阿努比斯
STDIO为AI智能体提供工作流指导的MCP服务器
为AI智能体提供工作流指导的MCP服务器
Transform your AI agent from chaotic coder to intelligent workflow orchestrator with three powerful capabilities:
NPM Package • Docker Hub • Website
Add to your MCP client config
{ "mcpServers": { "anubis": { "command": "npx", "args": ["-y", "@hive-academy/anubis"], "env": { "PROJECT_ROOT": "C:\\path\\to\\projects" } } } }
For Unix/Linux/macOS (mcp.json):
{ "mcpServers": { "anubis": { "command": "docker", "args": [ "run", "--rm", "-i", "-v", "${PWD}:/app/workspace", "-v", ".anubis:/app/.anubis", "hiveacademy/anubis" ] } } }
For Windows (mcp.json):
{ "mcpServers": { "anubis": { "command": "docker", "args": [ "run", "--rm", "-i", "-v", "C:\\path\\to\\your\\project:/app/workspace", "-v", "C:\\path\\to\\your\\project\\.anubis:/app/.anubis", "hiveacademy/anubis" ] } } }
Once you get the mcp server running you need to initialize the rules (custom-modes) for the agent you are using
Supported Agents: cursor • copilot • roocode • kilocode
Please initialize Anubis workflow rules for [your-agent-name] by calling the init_rules MCP tool
Begin a new workflow for [your-project] with Anubis guidance
1- install the MCP server:
{
  "mcpServers": {
    "anubis": {
      "command": "npx",
      "args": ["-y", "@hive-academy/anubis"],
      "env": {
        "PROJECT_ROOT": "C:\\path\\to\\projects"
      }
    }
  }
}
2- then make sure you are on Code mode and ask it to generate the custom Anubis mode for you
Please initialize Anubis workflow rules for roocode by calling the init_rules MCP tool
3- reload the window and you should see the custom mode in the modes dropdown list. activate it and ask it to create your first task
4- also if you don't have a memory bank files, ask it to generate them for you as the first task.
For Cursor users, here's a complete setup example:
Cmd/Ctrl + ,)"anubis": {
  "command": "npx",
  "args": ["-y", "@hive-academy/anubis"],
   "env": {
     "PROJECT_ROOT": "C:\\path\\to\\projects"
   }
}
Please initialize Anubis workflow rules for cursor by calling the init_rules MCP tool.000-workflow-core.mdcHint: an important first step task is to generate memory-bank files Ask the agent to
Please create a task to analyze codebase and generate memory-bank files (ProjectOverview.md, TechnicalArchitecture.md, and DeveloperGuide.md)
To install the mcp server use this command claude mcp add anubis npx -y @hive-academy/anubis
make sure you are on the poject root you want to install this into.
To make sure it's installed correctly run claude mcp list you should see a server with name anubis.
now you will need to do a very important step:
rules and file name anubis-rules.md.Anubis Workflow @rules/anubis-rules.md225% Completion Rate - Exceeded target goals by migrating 9 services (target: 4 services)
Successfully Migrated Services:
workflow-guidance.service.ts - Enhanced testability and maintainabilitystep-progress-tracker.service.ts - Clean state managementworkflow-bootstrap.service.ts - Simplified bootstrap processprogress-calculator.service.ts - Pure business logic functionsstep-query.service.ts - Flexible data access strategiesstep-execution.service.ts - Reliable execution trackingrole-transition.service.ts - Consistent role managementexecution-data-enricher.service.ts - Efficient data aggregationworkflow-guidance-mcp.service.ts - Standardized MCP operations95% Type Safety - Enhanced TypeScript compliance across the entire codebase
Zero Compilation Errors - Complete elimination of TypeScript build issues
75% Maintainability Improvement - Cleaner separation of concerns through repository pattern
Multi-Agent Support - Comprehensive template system for:
Database Optimization - 434,176 → 421,888 bytes (optimized storage)
Enhanced Query Performance - Repository pattern enables efficient data access
Improved State Management - ExecutionId-based workflow tracking
// Example: Service with Repository Pattern @Injectable() export class WorkflowGuidanceService { constructor( @Inject('IProjectContextRepository') private readonly projectContextRepository: IProjectContextRepository, @Inject('IWorkflowRoleRepository') private readonly workflowRoleRepository: IWorkflowRoleRepository, ) {} // 75% maintenance reduction through abstraction layer }
Repositories: WorkflowExecution • StepProgress • ProjectContext • WorkflowBootstrap • ProgressCalculation • WorkflowRole
Your AI agent receives step-by-step intelligent rules for every development task:
// Before Anubis: Chaotic, directionless coding "Create a user authentication system" → Where do I start? // With Anubis: Intelligent guidance at every step "Create a user authentication system" → Requirements Analysis (Researcher Role) System Architecture (Architect Role) Enhanced Implementation with Subtasks (Senior Dev Role) Quality Validation (Code Review Role) Delivery Preparation (Integration Engineer Role)
Benefits:
Never lose context when switching between roles or continuing tasks:
// Seamless context preservation across transitions { "currentRole": "architect", "completedSteps": ["requirements", "design"], "context": { "decisions": ["JWT for auth", "PostgreSQL for storage"], "rationale": "Scalability and security requirements", "nextSteps": ["Enhanced Implementation with Subtasks by Senior Dev role"] } } // → Switch roles without losing any context!
Features:
| Role | Intelligent Purpose | Key Powers | 
|---|---|---|
| Product Manager | Strategic Orchestration | Project setup, task creation, workflow management | 
| Architect | System Design | Technical architecture, implementation planning | 
| Senior Developer | Code Manifestation | High-quality implementation, testing | 
| Code Review | Quality Guardian | Security validation, performance review, approval | 
// 1. Agent receives intelligent guidance const guidance = await get_step_guidance({ executionId: 'auth-system-123', roleId: 'senior-developer' }); // 2. Anubis provides structured rules { "guidance": { "step": "Implement JWT authentication", "approach": [ "1. Create User model with Prisma", "2. Implement password hashing with bcrypt", "3. Create JWT token generation service", "4. Add authentication middleware" ], "qualityChecklist": [ "SOLID principles applied", "Unit tests coverage > 80%", "Security best practices", "Error handling implemented" ], "context": { "previousDecisions": ["PostgreSQL", "JWT strategy"], "nextRole": "code-review" } } } // 3. Agent executes with confidence and reports await report_step_completion({ result: 'success', metrics: { filesCreated: 8, testsWritten: 15, coverage: 85 } }); // 4. Quality delivery complete! ✅
Enterprise-Grade Architecture:
Production Ready:
# Development setup npm install && npm run db:init && npm run start:dev # Quality checks npm run test && npm run lint
Standards: MCP compliance • SOLID principles • Domain-driven design • Evidence-based development
MIT License - see LICENSE file for details.
Transform your AI workflows from chaotic to intelligent. Give your agents the rules of the ancients with modern MCP-compliant architecture.
Ready to ascend? Add Anubis to your MCP config now!