What can you do with this server?

This server provides a comprehensive platform for managing and utilizing specialized Claude AI agents for software development projects. * Project Analysis: Performs AI-powered analysis of project directories, assessing project type, complexity, and technology stack (often utilizing a CLAUDE.md file) * Agent Recommendations: Automatically recommends relevant agents based on project analysis, keywords, technology stack, missing capabilities, or development phase * Agent Search & Discovery: Search agents by keyword or name, list all available agents with category and language filters * Agent Management: Get detailed information about specific agents, install multiple agents to project directories, and refresh agent data from GitHub repository * Multi-language Support: Supports agents in multiple languages including English, Korean, Japanese, and Chinese * Analytics: Retrieve download statistics and usage data for agents

Which integrations are available for this server?

Supports frontend development with Angular through specialized sub-agents and project analysis Enables automatic agent downloading from the baryonlabs/claude-sub-agent-contents repository, providing offline caching and tracking of downloaded agents Offers project analysis and team composition recommendations optimized for Node.js applications Supports analysis and development of React components through specialized sub-agents for frontend development Provides specialized support for TypeScript projects through project analysis and role-specific agent recommendations Provides specialized game development support through the game developer sub-agent with Unity expertise

How do I use Claude Agents Power?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Claude Agents Power analyze my project and recommend which agents I need" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Claude Agents Power

by hongsw

Overview Schema Source Related Servers Discussions Admin

JavaScript

Hybrid

🤖 Claude Agents Power

English 한국어 License TypeScript MCP

🎯 Smart Role Assignment for Development Teams - An intelligent MCP server that analyzes your project and recommends the perfect team composition from 100+ professional roles across all company departments.

🚀 Quick Start with Claude

1️⃣ Install & Configure MCP Server

# Install via npm
npm install -g claude-agents-power

# Automatically configure Claude Desktop (NEW! 🎉)
# claude-agents-power --install

Or manually configure Claude Desktop:

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "claude-agents-power": {
      "command": "claude-agents-power"
    }
  }
}

2️⃣ Usage in Claude

Open Claude and try this example:

👤 User: "claude-agents-power를 이용해서 이 프로젝트를 위한 추천 및 agents/*.md 파일을 다운로드 해줘"

🤖 Claude: I'll analyze your project and download the recommended agents for you.

[Uses MCP tools to:]
1. 📊 Analyze your project structure 
2. 🎯 Recommend suitable roles
3. 📁 Download agents to ./claude/agents/
4. ✅ Ready to use sub-agents for your project!

3️⃣ Verify Installation

Check that agents were downloaded:

ls ./claude/agents/
# You should see downloaded .md files for recommended roles

4️⃣ Start Using Sub-Agents

Now you can use specialized roles in Claude:

"frontend-developer를 사용해서 React 컴포넌트를 만들어줘"
"data-scientist로 이 데이터를 분석해줘"  
"devops-engineer가 CI/CD 파이프라인을 설정해줘"

Related MCP server: AI-Persona

📖 Table of Contents

🌟 Features

🔍 Intelligent Project Analysis

Automatically detects project type, frameworks, and complexity
Provides smart role recommendations based on your tech stack
Supports multi-language projects and diverse architectures

👥 100+ Professional Roles

Technology & Engineering (20 roles): Frontend, Backend, DevOps, Security, AI/ML
Data & Analytics (15 roles): Data Scientists, Analysts, Engineers
Product & Design (10 roles): PM, UX/UI Designers, Researchers
Marketing & Sales (10 roles): Digital Marketing, Growth, Content
Operations & Management (15 roles): Project Managers, Operations
Finance & Accounting (10 roles): CFO, Controllers, Analysts
Human Resources (10 roles): Talent Acquisition, L&D, Culture
Executive & Leadership (10 roles): C-Level executives and strategy

🌐 Multi-Language Support

English: Global standards and international projects
한국어: Korean business context and local practices

⚡ Claude Code Integration

Seamless integration with Claude Code via MCP protocol
Real-time role recommendations and team composition
One-click agent installation to your project

🌐 GitHub Integration

Automatic agent downloading from baryonlabs/claude-sub-agent-contents
Download tracking and usage analytics
Offline caching for downloaded agents
Installs to ./claude/agents/ directory structure
No need to create agent templates from scratch

🚀 Development Setup

Build from Source

# Clone the repository
git clone https://github.com/hongsw/claude-agents-power-mcp-server.git
cd claude-agents-power

# Install dependencies
npm install

# Build the project
npm run build

MCP Configuration for Development

Add to your ~/.config/claude/mcp_servers.json:

{
  "mcpServers": {
    "claude-agents-power": {
      "command": "node",
      "args": ["/path/to/claude-agents-power/dist/index.js"],
      "cwd": "/path/to/your/project",
      "env": {
        "GITHUB_TOKEN": "your_github_token_here"
      }
    }
  }
}

Analytics & Telemetry

This tool includes anonymous usage analytics (telemetry) to help improve the user experience and identify common usage patterns. The telemetry system:

What is collected: Tool usage patterns, command frequency, error rates (no personal data)
What is NOT collected: File contents, agent data, GitHub tokens, or any personally identifiable information
Purpose: Understanding which features are most used, identifying common errors, improving performance
Technology: Uses PostHog with a public API key that can only send events, not read data

Disabling Telemetry

If you prefer not to send anonymous usage data, you can disable telemetry using either of these methods:

# Method 1: Environment variable
export DISABLE_TELEMETRY=true

# Method 2: In your .env file
DISABLE_TELEMETRY=true

# Alternative (also works)
DISABLE_ANALYTICS=true

Telemetry vs OpenTelemetry

This project uses product analytics telemetry (PostHog), not OpenTelemetry:

Product Analytics Telemetry: Tracks user interactions, feature usage, and product metrics
OpenTelemetry: Industry standard for distributed tracing, metrics, and logs in microservices

While both involve "telemetry", they serve different purposes. Our telemetry helps understand how the tool is used to improve the user experience, not for system monitoring or performance tracing.

Environment Variables

Configure these optional environment variables for enhanced functionality:

Method 1: Using .env file (Recommended for local development)

Copy the example environment file:
```
cp .env.example .env
```

Edit .env and add your GitHub token:

# GitHub Personal Access Token (required for auto issue creation)
GITHUB_TOKEN=ghp_your_actual_token_here

# To disable analytics, uncomment:
# DISABLE_ANALYTICS=true

Method 2: Using MCP configuration

Add environment variables directly to your MCP server configuration as shown above.

Available Variables

GITHUB_TOKEN: GitHub personal access token for automatic issue creation when agents are not found
- Create at: https://github.com/settings/tokens
- Required permissions: public_repo or repo (for private repos)
DISABLE_TELEMETRY or DISABLE_ANALYTICS: Set to true to disable anonymous usage telemetry
- Telemetry is enabled by default to help improve the tool
- No personal data is collected, only anonymous usage metrics
- Example: DISABLE_TELEMETRY=true
POSTHOG_API_KEY: Custom PostHog API key (optional)
- The tool includes a default public key for analytics
- Only set if you want to use your own PostHog project
POSTHOG_HOST: PostHog instance URL (defaults to https://app.posthog.com)
- Only needed if using a self-hosted PostHog instance

MCP Tools Reference

# Analyze your current project
mcp__claude-agents-power__analyze-project

# Get role recommendations  
mcp__claude-agents-power__recommend-by-keywords ["web", "api", "database"]

# Install recommended agents
mcp__claude-agents-power__install-agents ["frontend-developer", "backend-developer"]

📋 Available Roles

🔧 Technology & Engineering (20 roles)

Role	English	한국어	Tools	Specialization
Software Engineer	EN	KO	`Bash, Read, Write, Edit`	Full-stack development, system design
Frontend Developer	EN	KO	`Read, Write, Edit, Bash`	React, Vue, Angular, UI/UX
Backend Developer	EN	KO	`Bash, Read, Write, Edit`	APIs, databases, server architecture
DevOps Engineer	EN	KO	`Bash, Read, Write`	CI/CD, infrastructure automation
Data Engineer	EN	KO	`Bash, Read, Write`	ETL pipelines, data architecture

Role	English	한국어	Tools	Specialization
ML Engineer	EN	KO	`Bash, Read, Write`	Model deployment, MLOps
Security Engineer	EN	KO	`Bash, Read, Grep`	Cybersecurity, threat analysis
Cloud Architect	EN	KO	`Bash, Read, Write`	AWS, Azure, GCP architecture
Mobile Developer	EN	KO	`Read, Write, Edit, Bash`	iOS, Android, React Native
QA Engineer	EN	KO	`Bash, Read, Write`	Test automation, quality assurance
Database Administrator	EN	KO	`Bash, Read, Write`	Database optimization, backup
Network Engineer	EN	KO	`Bash, Read, Write`	Network infrastructure, security
Site Reliability Engineer	EN	KO	`Bash, Read, Write`	System reliability, monitoring
Blockchain Developer	EN	KO	`Read, Write, Edit`	Smart contracts, DeFi
Game Developer	EN	KO	`Read, Write, Edit`	Unity, Unreal, game engines
Embedded Systems Engineer	EN	KO	`Read, Write, Bash`	IoT, firmware, hardware
Technical Writer	EN	KO	`Read, Write, Edit`	Documentation, API docs
Solution Architect	EN	KO	`Read, Write, Bash`	System integration, design
AI Researcher	EN	KO	`Read, Write, Bash`	Research, algorithm development
Tech Lead	EN	KO	`Read, Write, Edit, Bash`	Team leadership, architecture

📊 Data & Analytics (15 roles)

Role	English	한국어	Tools	Specialization
Data Scientist	EN	KO	`Bash, Read, Write`	ML modeling, statistical analysis
Data Analyst	EN	KO	`Read, Write, Bash`	Business insights, reporting
Business Intelligence Analyst	EN	KO	`Read, Write, Bash`	Dashboards, BI tools
Quantitative Analyst	EN	KO	`Read, Write, Bash`	Financial modeling, risk analysis
Research Analyst	EN	KO	`Read, Write`	Market research, competitive analysis

Role	English	한국어	Tools	Specialization
Analytics Engineer	EN	KO	`Bash, Read, Write`	Data infrastructure, modeling
Marketing Analyst	EN	KO	`Read, Write`	Campaign optimization, metrics
Financial Analyst	EN	KO	`Read, Write`	Financial planning, forecasting
Operations Analyst	EN	KO	`Read, Write, Bash`	Process optimization, efficiency
Product Analyst	EN	KO	`Read, Write`	User behavior, product metrics
Risk Analyst	EN	KO	`Read, Write`	Risk assessment, mitigation
Growth Analyst	EN	KO	`Read, Write`	Growth metrics, experimentation
Customer Insights Analyst	EN	KO	`Read, Write`	Customer segmentation, behavior
Pricing Analyst	EN	KO	`Read, Write`	Pricing strategy, revenue optimization
Supply Chain Analyst	EN	KO	`Read, Write, Bash`	Supply chain optimization

🎨 Product & Design (10 roles)

Role	English	한국어	Tools	Specialization
Product Manager	EN	KO	`Read, Write`	Product strategy, roadmap
Product Designer	EN	KO	`Read, Write`	User experience, product design
UX Designer	EN	KO	`Read, Write`	User research, wireframes
UI Designer	EN	KO	`Read, Write`	Visual design, prototypes
Graphic Designer	EN	KO	`Read, Write`	Brand identity, visual assets

Role	English	한국어	Tools	Specialization
UX Researcher	EN	KO	`Read, Write`	User research, usability testing
Product Owner	EN	KO	`Read, Write`	Backlog management, scrum
Design Lead	EN	KO	`Read, Write`	Design system, team leadership
Creative Director	EN	KO	`Read, Write`	Creative strategy, brand vision
Interaction Designer	EN	KO	`Read, Write`	Interaction design, prototyping

📈 Marketing & Sales (10 roles)

Role	English	한국어	Tools	Specialization
Marketing Manager	EN	KO	`Read, Write`	Marketing strategy, campaigns
Sales Manager	EN	KO	`Read, Write`	Sales strategy, team management
Digital Marketing Specialist	EN	KO	`Read, Write`	Online advertising, SEO/SEM
Content Marketing Manager	EN	KO	`Read, Write`	Content strategy, creation
Social Media Manager	EN	KO	`Read, Write`	Social media strategy, community

Role	English	한국어	Tools	Specialization
SEO Specialist	EN	KO	`Read, Write, Grep`	Search optimization, analytics
Brand Manager	EN	KO	`Read, Write`	Brand strategy, positioning
Growth Marketing Manager	EN	KO	`Read, Write`	Growth hacking, experiments
Account Manager	EN	KO	`Read, Write`	Client relations, account growth
Business Development Manager	EN	KO	`Read, Write`	Partnerships, business growth

⚙️ Operations & Management (15 roles)

Role	English	한국어	Tools	Specialization
Operations Manager	EN	KO	`Read, Write, Bash`	Process optimization, efficiency
Project Manager	EN	KO	`Read, Write`	Project planning, coordination
Program Manager	EN	KO	`Read, Write`	Multi-project coordination
Supply Chain Manager	EN	KO	`Read, Write`	Supply chain optimization
Quality Assurance Manager	EN	KO	`Read, Write, Bash`	Quality processes, improvement

Role	English	한국어	Tools	Specialization
Facilities Manager	EN	KO	`Read, Write`	Facility management, workplace
Procurement Manager	EN	KO	`Read, Write`	Vendor relations, purchasing
Logistics Manager	EN	KO	`Read, Write`	Logistics, delivery optimization
Inventory Manager	EN	KO	`Read, Write`	Inventory control, forecasting
Production Manager	EN	KO	`Read, Write, Bash`	Manufacturing, production
Change Management Specialist	EN	KO	`Read, Write`	Organizational change
Business Process Analyst	EN	KO	`Read, Write`	Process analysis, improvement
Vendor Manager	EN	KO	`Read, Write`	Vendor management, contracts
Compliance Manager	EN	KO	`Read, Write`	Regulatory compliance
Agile Coach	EN	KO	`Read, Write`	Agile methodology, coaching

💰 Finance & Accounting (10 roles)

Role	English	한국어	Tools	Specialization
Chief Financial Officer	EN	KO	`Read, Write`	Financial strategy, corporate finance
Financial Controller	EN	KO	`Read, Write`	Financial control, reporting
Accounting Manager	EN	KO	`Read, Write`	Accounting operations
Treasury Manager	EN	KO	`Read, Write`	Cash management, treasury
Tax Manager	EN	KO	`Read, Write`	Tax strategy, compliance

Role	English	한국어	Tools	Specialization
Internal Auditor	EN	KO	`Read, Write, Grep`	Internal audit, risk assessment
Budget Analyst	EN	KO	`Read, Write`	Budget planning, analysis
Investment Analyst	EN	KO	`Read, Write`	Investment analysis, portfolio
Credit Analyst	EN	KO	`Read, Write`	Credit risk, assessment
Payroll Manager	EN	KO	`Read, Write`	Payroll systems, compensation

👥 Human Resources (10 roles)

Role	English	한국어	Tools	Specialization
HR Manager	EN	KO	`Read, Write`	HR strategy, people management
Talent Acquisition Specialist	EN	KO	`Read, Write`	Recruitment, talent sourcing
HR Business Partner	EN	KO	`Read, Write`	Strategic HR, business alignment
Compensation & Benefits Manager	EN	KO	`Read, Write`	Compensation design, benefits
Learning & Development Manager	EN	KO	`Read, Write`	Training programs, development

Role	English	한국어	Tools	Specialization
Employee Relations Manager	EN	KO	`Read, Write`	Employee relations, conflict resolution
Organizational Development Manager	EN	KO	`Read, Write`	Organization design, change
Diversity & Inclusion Manager	EN	KO	`Read, Write`	D&I strategy, inclusive culture
HR Analyst	EN	KO	`Read, Write`	HR metrics, workforce analytics
Employee Experience Manager	EN	KO	`Read, Write`	Employee journey, culture

🏢 Executive & Leadership (10 roles)

Role	English	한국어	Tools	Specialization
Chief Executive Officer	EN	KO	`Read, Write`	Corporate strategy, leadership
Chief Operating Officer	EN	KO	`Read, Write, Bash`	Operations, execution
Chief Technology Officer	EN	KO	`Read, Write, Edit, Bash`	Technology strategy, innovation
Chief Marketing Officer	EN	KO	`Read, Write`	Marketing strategy, brand
Chief Product Officer	EN	KO	`Read, Write`	Product strategy, innovation

Role	English	한국어	Tools	Specialization
Chief Data Officer	EN	KO	`Read, Write, Bash`	Data strategy, governance
Chief Information Officer	EN	KO	`Read, Write, Bash`	IT strategy, systems
Chief Human Resources Officer	EN	KO	`Read, Write`	HR strategy, culture
Chief Revenue Officer	EN	KO	`Read, Write`	Revenue strategy, growth
Chief Strategy Officer	EN	KO	`Read, Write`	Corporate strategy, planning

⚡ Slash Commands (NEW!)

Claude Agents Power now supports convenient slash commands in Claude Code, similar to SuperClaude Framework!

🚀 Installation

Install slash commands to Claude Code:

npx claude-agents-power --install-slash-commands

📋 Available Commands

Once installed, you can use these commands directly in Claude Code:

`/agents:load [language] [role] [--flags]`

Load and display available agents

/agents:load                    # Show all agents
/agents:load ko                 # Show Korean agents
/agents:load backend-engineer   # Show specific role
/agents:load --all --detailed   # Show all with descriptions

`/agents:search <query> [--flags]`

Search for agents by skills or keywords

/agents:search "machine learning"
/agents:search "frontend react" --language en
/agents:search "데이터 분석" --language ko --fuzzy

`/agents:suggest [context] [--flags]`

Get intelligent agent recommendations

/agents:suggest                                    # Auto-detect from project
/agents:suggest "building React e-commerce"
/agents:suggest --project-type web --phase development

`/agents:version [--flags]`

Check system version and status

/agents:version                    # Basic version info
/agents:version --detailed         # System details
/agents:version --check-updates    # Check for updates

`/agent-download [--flags]` ⭐ NEW!

Automatically analyze project and download recommended agents

/agent-download                                    # Auto-analyze and download
/agent-download --target-dir ./team --limit 5     # Custom directory and limit
/agent-download --dry-run                          # Preview only
/agent-download --language ko --format yaml       # Korean agents in YAML format

🗑️ Uninstallation

Remove slash commands:

npx claude-agents-power --uninstall-slash-commands

💡 Pro Tips

Start with /agents:load to see all available agents
Use /agents:suggest for context-aware recommendations
Try /agents:search when you know what skills you need
Check /agents:version if agents aren't loading properly

🎯 Usage Examples

📊 Download Statistics

# Get download statistics for popular agents
mcp__claude-agents-power__get-download-stats

# Refresh agents from GitHub repository
mcp__claude-agents-power__refresh-agents

🚀 Startup MVP Development

# Analyze project and get recommendations
mcp__claude-agents-power__analyze-project

# Install core startup team
mcp__claude-agents-power__install-agents [
  "product-manager",
  "frontend-developer", 
  "backend-developer",
  "growth-marketing-manager"
]

🏢 Enterprise Application

# Get recommendations for enterprise project
mcp__claude-agents-power__recommend-by-keywords [
  "enterprise", "security", "scalability", "compliance"
]

# Install enterprise team
mcp__claude-agents-power__install-agents [
  "solution-architect",
  "security-engineer",
  "devops-engineer",
  "compliance-manager"
]

📊 Data Platform

# Search for data-related roles
mcp__claude-agents-power__search-agents "data analytics machine learning"

# Install data team
mcp__claude-agents-power__install-agents [
  "data-scientist",
  "data-engineer", 
  "machine-learning-engineer",
  "analytics-engineer"
]

📚 Documentation

📖 User Guides

User Guide - Complete usage guide with best practices
Examples - Real-world scenarios and use cases
Troubleshooting - Common issues and solutions

🔧 Technical Documentation

Installation Guide - Step-by-step setup instructions

🛠️ Development

Prerequisites

Node.js 16+
TypeScript 5+
Claude Code with MCP support

Build from Source

git clone https://github.com/hongsw/claude-agents-power-mcp-server.git
cd claude-agents-power
npm install
npm run build
npm test

Project Structure

claude-agents-power/
├── src/                    # TypeScript source code
├── claude/agents/         # Agent definitions
│   ├── en/               # English agents (85 roles)
│   ├── kr/               # Korean agents (85 roles)
│   ├── ja/               # Japanese agents (5 roles)
│   └── zh/               # Chinese agents (8 roles)
├── sub-agents/            # Legacy agent definitions (deprecated)
├── dist/                 # Compiled JavaScript
├── docs/                 # Documentation
└── examples/             # Usage examples

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

🌟 How to Contribute

Add New Roles - Create agents for specialized positions
Improve Translations - Enhance Korean/English localization
Add Project Templates - Contribute industry-specific templates
Documentation - Improve guides and examples

🔍 Can't Find the Agent You Need?

If you can't find a specific agent role you're looking for, here's how to request or create one:

📋 Request a New Agent

Check Existing Agents First

# Search for agents using MCP
claude-agents-power agents --action search --query "your-role"

Automatic Issue Creation (NEW! 🎉)

# Automatically create GitHub Issue when search returns 0 results
# Requires GITHUB_TOKEN environment variable
export GITHUB_TOKEN=your_github_token

# Enable auto issue creation when searching
claude-agents-power agents --action search --query "blockchain-architect" --autoCreateIssue true

# Or directly create an issue
claude-agents-power agents --action request --name "blockchain-architect" --description "Blockchain system design expert"

Manual Issue Submission
- Go to GitHub Issues
- Click "New Issue"
- Use title format: [Agent Request] Role Name - Brief Description
- Include:
  - Role name (e.g., blockchain-architect)
  - Description of responsibilities
  - Required tools
  - Use cases

🛠️ Create Your Own Agent

Agent File Format

Create a new .md file in claude/agents/{language}/ directory:

---
name: your-agent-name
description: Brief description of the agent's expertise and responsibilities
tools: Read, Write, Edit, Bash, WebSearch
---

You are a [role title] specializing in [domain/expertise].

## Core Responsibilities
- Primary responsibility 1
- Primary responsibility 2
- Primary responsibility 3

## Key Practices
- Best practice or methodology 1
- Best practice or methodology 2
- Best practice or methodology 3

## Tools and Technologies
- Specific tools or frameworks used
- Technologies you're expert in
- Platforms you work with

## Quality Standards
- Quality metric or standard 1
- Quality metric or standard 2
- Performance expectations

Available Tools

Choose appropriate tools for your agent:

Read, Write, Edit, MultiEdit - File operations
Bash, Grep, Glob - System operations
WebSearch, WebFetch - Internet access
TodoWrite, Task - Task management
NotebookRead, NotebookEdit - Jupyter notebook support

Example: Creating a Blockchain Architect Agent

claude/agents/en/blockchain-architect.md:

---
name: blockchain-architect
description: Blockchain system architect designing scalable DLT solutions and smart contract architectures
tools: Read, Write, Edit, Bash, WebSearch
---

You are a blockchain architect specializing in distributed ledger technology and decentralized systems.

## Core Responsibilities
- Design blockchain network architectures
- Develop smart contract systems
- Implement consensus mechanisms
- Ensure security and scalability

## Key Practices
- Follow security-first design principles
- Optimize for gas efficiency
- Implement proper access controls
- Design upgradeable contracts
- Ensure cross-chain compatibility

## Tools and Technologies
- Ethereum, Polygon, Solana
- Solidity, Rust, Move
- Web3.js, Ethers.js
- Hardhat, Truffle, Foundry
- IPFS, The Graph

## Quality Standards
- 100% test coverage for smart contracts
- Gas optimization benchmarks
- Security audit compliance
- Formal verification when applicable

📤 Submit Your Agent

Fork the Repository

git clone https://github.com/hongsw/claude-agents-power-mcp-server.git
cd claude-agents-power-mcp-server

Create Your Agent File

# For English agents
touch claude/agents/en/your-agent-name.md

# For Korean agents
touch claude/agents/ko/your-agent-name.md

Submit a Pull Request
- Commit your changes
- Push to your fork
- Create a PR with description
- We'll review and merge!

💡 Agent Creation Tips

Be Specific: Clearly define the role's expertise and boundaries
Choose Tools Wisely: Only include tools the agent actually needs
Include Examples: Add specific methodologies or frameworks
Consider Localization: Provide translations for multiple languages
Test Your Agent: Ensure it works well with real tasks

🚀 Roadmap

GitHub integration for agent templates
Download tracking and analytics
Visual project analyzer dashboard
Role dependency recommendations
Industry-specific role bundles
Integration with popular project management tools
Advanced team composition algorithms

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

⭐ Star this repository if you find it useful!

🐛 Report Bug • ✨ Request Feature • 📖 Documentation

Made with ❤️ for the Claude Code community

Available Tools

8 tools

analyze-projectC

Analyze a project directory and recommend suitable sub-agents

ParametersJSON Schema

Name	Required	Description	Default
`projectPath`	Yes	Path to the project directory to analyze

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions analysis and recommendation but does not describe how the analysis is performed (e.g., scanning files, detecting dependencies), what the output looks like (e.g., list of agents with reasons), or any constraints like performance impact or permissions needed. This is a significant gap for a tool with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It is front-loaded and every part of the sentence contributes to understanding the tool's function, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of analyzing a project and recommending agents, the description is incomplete. It lacks details on the analysis method, output format (no output schema provided), and behavioral traits. With no annotations and an output schema missing, the description does not provide enough context for the agent to understand the full scope and implications of using this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the single parameter 'projectPath' clearly documented in the schema as 'Path to the project directory to analyze'. The description does not add any additional meaning beyond this, such as format examples or constraints, so it meets the baseline of 3 where the schema handles the parameter documentation adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('analyze a project directory') and the outcome ('recommend suitable sub-agents'), which is specific and actionable. However, it does not explicitly differentiate this tool from sibling tools like 'recommend-by-keywords' or 'search-agents', which might have overlapping functionality, preventing a score of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. For example, it does not specify if this is for initial project setup, ongoing analysis, or how it differs from 'recommend-by-keywords' or 'search-agents'. This lack of context leaves the agent without clear usage instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get-agent-detailsC

Get detailed information about a specific agent

ParametersJSON Schema

Name	Required	Description	Default
`agentName`	Yes	Name of the agent (e.g., frontend-developer)
`language`	No	Language preference (en, kr)	en

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get detailed information' implies a read-only operation, it doesn't specify what 'detailed information' includes, whether authentication is required, potential rate limits, or error conditions. This leaves significant gaps for an agent to understand the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no wasted words. It's front-loaded with the core purpose ('Get detailed information'), making it easy to parse. Every word earns its place by conveying essential intent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'detailed information' entails (e.g., metadata, capabilities, status), which is critical for a tool with no structured output definition. This leaves the agent guessing about the return value and usage context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents both parameters (agentName and language). The description doesn't add any parameter-specific details beyond what's in the schema, such as clarifying the format of 'detailed information' returned. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get detailed information') and resource ('about a specific agent'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'list-agents' or 'search-agents', which likely provide different types of agent information.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when this tool is appropriate (e.g., for detailed metadata vs. basic listings) or when to choose siblings like 'list-agents' (for summaries) or 'search-agents' (for filtering).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get-download-statsC

Get download statistics for agents

ParametersJSON Schema

Name	Required	Description	Default
`limit`	No	Number of top agents to show

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool's function but lacks critical details such as whether it requires authentication, has rate limits, returns paginated results, or what format the statistics are in (e.g., counts, trends). This leaves significant gaps for an agent to understand how to interact with it effectively.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any redundant or unnecessary words. It is appropriately sized and front-loaded, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the download statistics include (e.g., time ranges, metrics), how results are structured, or any behavioral traits like error handling. For a tool with no structured output information, more context is needed to guide the agent fully.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with the 'limit' parameter clearly documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, such as explaining what 'download statistics' entail or how the limit affects ranking. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get download statistics') and the resource ('for agents'), which is specific and unambiguous. However, it doesn't differentiate from sibling tools like 'get-agent-details' or 'list-agents' that might also provide agent-related information, preventing a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. For example, it doesn't specify if this is for aggregated stats versus detailed per-agent data, or how it differs from siblings like 'get-agent-details' or 'list-agents', leaving the agent to infer usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

install-agentsC

Install multiple sub-agents to a project directory

ParametersJSON Schema

Name	Required	Description	Default
`agentNames`	Yes	List of agent names to install
`language`	No	Language preference for agents (en, kr)	en
`targetPath`	Yes	Target project directory path

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action is 'install' but doesn't specify whether this is a write operation, requires permissions, has side effects like overwriting files, or involves network calls. This leaves critical behavioral traits undocumented for a tool that likely modifies a system.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized, making it easy to grasp quickly without any wasted information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of installing agents (likely involving file system changes and network operations), no annotations, and no output schema, the description is insufficient. It lacks details on behavior, error handling, or what happens post-installation, making it incomplete for safe and effective use by an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds no parameter-specific information beyond what the input schema provides. Since schema description coverage is 100%, the baseline score is 3. The description doesn't elaborate on parameter meanings, such as what 'agentNames' represent or how 'targetPath' is validated, but the schema adequately covers these details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('install') and target ('multiple sub-agents to a project directory'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'refresh-agents' or 'list-agents', which could involve similar resources but different operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing an existing project directory, or compare it to siblings like 'refresh-agents' for updates or 'list-agents' for viewing installed agents, leaving usage context unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list-agentsB

List all available agents

ParametersJSON Schema

Name	Required	Description	Default
`category`	No	Filter by category
`language`	No	Language preference (en, kr)	en

TDQS

B3.1/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a list operation, implying read-only behavior, but doesn't cover aspects like pagination, rate limits, authentication requirements, or what 'available' means in context. For a tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no wasted words. It's front-loaded with the core purpose and appropriately sized for a simple list operation, making it highly efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (a filtered list operation) and high schema coverage, the description is minimally adequate. However, with no output schema and no annotations, it should ideally provide more context about return values or behavioral traits to be fully complete for agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with both parameters ('category' and 'language') well-documented in the input schema. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline for adequate but not enhanced parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'List all available agents' clearly states the action (list) and resource (agents), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'search-agents' or 'get-agent-details', which would require more specificity about scope or filtering capabilities.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'search-agents' or 'get-agent-details'. There's no mention of prerequisites, context for filtering, or comparison with sibling tools, leaving the agent to infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

recommend-by-keywordsC

Recommend agents based on project keywords

ParametersJSON Schema

Name	Required	Description	Default
`keywords`	Yes	List of project keywords (e.g., api, database, ui)

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It states the tool 'recommends' agents, implying a read-only operation, but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns structured data, or how recommendations are generated (e.g., based on a database or algorithm).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste, front-loading the key action ('Recommend agents') and context ('based on project keywords'). It's appropriately sized for a simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a list of agents with details, scores, or just names), how recommendations are ranked, or any error conditions, leaving gaps for a tool that likely involves data processing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the parameter 'keywords' well-documented in the schema as 'List of project keywords (e.g., api, database, ui)'. The description adds no additional meaning beyond this, so it meets the baseline of 3 for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Recommend') and resource ('agents') with the context ('based on project keywords'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'search-agents' or 'list-agents', which might offer similar functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as 'search-agents' or 'list-agents'. The description implies usage for keyword-based recommendations but lacks explicit when/when-not instructions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

refresh-agentsB

Refresh agents from GitHub repository

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

B3.1/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. 'Refresh agents from GitHub repository' implies a write/mutation operation (updating existing agents), but doesn't specify what gets updated, whether this requires authentication, what happens to existing configurations, or potential side effects. For a tool that likely modifies system state, this is insufficient behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It's appropriately sized for a zero-parameter tool and gets straight to the point without unnecessary elaboration. Every word contributes to understanding the tool's purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool that likely performs mutations (refreshing/updating agents), the description is incomplete. With no annotations, no output schema, and minimal behavioral context, important information is missing: what 'refresh' entails, success/failure conditions, authentication requirements, and how this differs from installation. The description doesn't provide enough context for safe, effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description doesn't need to compensate for any parameter gaps. A baseline of 4 is appropriate since there are no parameters to explain beyond what the empty schema already indicates.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Refresh') and resource ('agents from GitHub repository'), making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'install-agents' or 'list-agents' - both could involve GitHub repository operations. The description lacks specificity about what 'refresh' means in this context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives. With siblings like 'install-agents', 'list-agents', and 'get-agent-details', there's no indication of when refreshing is appropriate versus installing, listing, or getting details. The description offers no context about prerequisites, timing, or relationship to other operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search-agentsC

Search for agents by keyword or name

ParametersJSON Schema

Name	Required	Description	Default
`language`	No	Language preference (en, kr)	en
`query`	Yes	Search query for agents

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It states the tool searches for agents but doesn't disclose behavioral traits such as whether it's read-only (likely, but not confirmed), how results are returned (e.g., pagination, format), or any limitations (e.g., rate limits, authentication needs). This is a significant gap for a search tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for a simple search tool, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (a search tool with 2 parameters), no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a list of agents, their details), how results are structured, or any behavioral constraints. This leaves gaps for an AI agent to use the tool effectively without additional context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters ('query' for search and 'language' with enum values). The description adds minimal value beyond the schema by implying the 'query' parameter is for 'keyword or name' searching, but it doesn't provide additional syntax, format details, or context beyond what the schema specifies. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Search for agents') and resource ('agents'), specifying it's by 'keyword or name'. It distinguishes from siblings like 'list-agents' (which presumably lists without search) and 'get-agent-details' (which gets details for a specific agent). However, it doesn't explicitly differentiate from 'recommend-by-keywords', which might be a more specific recommendation tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention when to prefer 'search-agents' over 'list-agents' (e.g., for filtered results) or 'recommend-by-keywords' (e.g., for recommendations vs. general search). The description implies usage for searching but lacks explicit context or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

8 tool updatesv1.0.0Jul 27, 2025
- First observedanalyze-project
- First observedget-agent-details
- First observedget-download-stats
- First observedinstall-agents
- First observedlist-agents
- First observedrecommend-by-keywords
- First observedrefresh-agents
- First observedsearch-agents

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.4/5.0

Scored 2026-04-18 09:15 across 8 tools

Disambiguation4/5

Most tools have distinct purposes, but 'search-agents' and 'recommend-by-keywords' could cause some confusion as both involve finding agents based on keywords. However, their descriptions clarify that 'search-agents' is for direct keyword/name matching while 'recommend-by-keywords' is for project-based recommendations, which helps mitigate overlap.

Naming Consistency5/5

All tools follow a consistent verb_noun naming pattern with hyphens (e.g., 'analyze-project', 'list-agents', 'install-agents'). There are no deviations in style or convention, making the set highly predictable and readable.

Tool Count5/5

With 8 tools, this server is well-scoped for managing and discovering agents. The count is appropriate for the domain, providing essential operations like listing, searching, installing, and analyzing without being overwhelming or insufficient.

Completeness4/5

The tool set covers core workflows for agent management, including discovery (list, search, recommend), installation, and analysis. A minor gap is the lack of tools for updating or uninstalling agents, which could limit lifecycle management, but agents can still perform basic operations effectively.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

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🤖 Claude Agents Power

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2️⃣ Usage in Claude

3️⃣ Verify Installation

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📖 Table of Contents

🌟 Features

🔍 Intelligent Project Analysis

👥 100+ Professional Roles

🌐 Multi-Language Support

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`/agents:load [language] [role] [--flags]`

`/agents:search <query> [--flags]`

`/agents:suggest [context] [--flags]`

`/agents:version [--flags]`

`/agent-download [--flags]` ⭐ NEW!