Mcp Skill Creator Agency

SkillCreatorAgency – Agency Swarm Starter

A production-ready starter for running a single-agent Agency Swarm setup that uses a standalone Claude Skills MCP backend and a skill_creator agent for managing skills and tools.

---

🚀 Quick Start

1. Install Dependencies

pip install -r requirements.txt

2. Set Up Environment Variables

Create a .env file in the root directory:

# Required
OPENAI_API_KEY=your_openai_api_key_here

# Optional - Add any additional API keys your agents need
# EXAMPLE_API_KEY=your_api_key_here

3. Run the standalone Claude Skills MCP backend

In one terminal:

source venv/bin/activate
python scripts/start_claude_skills_mcp.py

This starts the claude-skills-mcp-backend HTTP MCP server (vector search, sentence-transformers, PyTorch, etc.) using claude-skills-mcp-config.json and loading skills from mnt/skills.

Leave this terminal running.

4. Run the SkillCreatorAgency

In another terminal:

source venv/bin/activate
python agency.py

agency.py only connects to the already-running MCP backend; it will not attempt to start it. If the backend is not detected, it prints instructions on how to start it and exits.

---

🧩 Using the SkillCreatorAgency to Build New Skills

Once both the Claude Skills backend and the agency are running, you can use the terminal UI to create and iterate on skills.

1. Inspect existing skills

In the interactive terminal started by python agency.py, you can simply ask:

• What skills are available?

The skill_creator agent will:

• Call Claude_Skills.find_helpful_skills to semantically search for relevant skills.
• Call Claude_Skills.list_skills to show the full inventory, including:
• Skill names
• Short descriptions
• Source paths under mnt/skills.

2. Create a new skill (e.g. reporting-skill)

Example conversation:

• You: I want to create a new reporting skill.
• Agent:
• Uses the skill-creator skill to plan the new skill.
• Asks a short set of questions (name, description, data sources, outputs, delivery, etc.).
• You can answer in detail or say: use defaults.

Under the hood, the agent will:

• Run python3 ./mnt/skills/skill-creator/scripts/init_skill.py --path ./mnt/skills/

via the PersistentShellTool.

• Initialize a new skill folder like:

• mnt/skills/reporting-skill/
• SKILL.md
• scripts/
• references/
• assets/

• Optionally overwrite SKILL.md and add starter scripts such as:

• scripts/generate_report.py – data in (CSV/SQLite), reports out (CSV/XLSX/PDF), optional email.

3. Iterate on the new skill

From there you can:

• Ask the agent to:
• Open or modify SKILL.md.
• Edit or add scripts under scripts/.
• Add reference docs or assets.
• Use the built-in validation and packaging scripts from the skill-creator skill:

``bash python3 ./mnt/skills/skill-creator/scripts/quick_validate.py ./mnt/skills// python3 ./mnt/skills/skill-creator/scripts/package_skill.py ./mnt/skills// ./dist ``

This pattern works for any new skill you want to build (reporting, PDF processing, dashboards, etc.): you describe the skill conversationally, and the skill_creator agent orchestrates init_skill.py, file edits, validation, and packaging for you.

---

🏗️ Project Structure

agency-starter-template/
├── agency.py                 # Main entry point (SkillCreatorAgency)
├── main.py                   # FastAPI integration entrypoint (do not modify)
├── requirements.txt          # Python dependencies
├── Dockerfile                # Container configuration
├── .env                      # Environment variables (create this)
├── AGENTS.md                 # Agent-creation workflow and instructions
├── shared_instructions.md    # Shared instructions for the agency
├── claude-skills-mcp-config.json   # Backend config (skills, embeddings, etc.)
├── scripts/
│   └── start_claude_skills_mcp.py  # Script to start standalone MCP backend
├── skill_creator/
│   ├── __init__.py
│   ├── skill_creator.py      # `skill_creator` Agent definition
│   ├── instructions.md       # Agent-specific instructions
│   ├── files/                # Local files accessible to the agent
│   └── tools/
│       └── __init__.py
├── servers/
│   └── claude_skills/        # Thin Python wrappers around Claude Skills MCP tools
│       ├── __init__.py
│       ├── find_helpful_skills.py
│       ├── list_skills.py
│       ├── read_skill_document.py
│       └── server.py
├── mnt/
│   └── skills/
│       └── skill-creator/    # Local skill for this repo
│           ├── SKILL.md
│           ├── LICENSE.txt
│           └── scripts/
│               ├── init_skill.py
│               ├── package_skill.py
│               └── quick_validate.py
├── tests/
│   ├── test_agency.py
│   └── test_claude_skills.py
└── venv/                     # Local virtualenv (not committed)

---

🔧 Creating Your Own Agency

🤖 AI-Assisted Agency Creation with Cursor

This template includes AI-powered agency creation using Cursor IDE:

1. Open this project in Cursor IDE

1. Use the AI Assistant to create your agency by referencing:

`` 📁 .cursor/rules/workflow.mdc ``

1. Simply ask the AI:

> "Create a new agency using the .cursor workflow"

The AI will guide you through the complete 7-step process:

• ✅ PRD Creation
• ✅ Folder Structure Setup
• ✅ Tool Development
• ✅ Agent Creation
• ✅ Agency Configuration
• ✅ Testing & Validation
• ✅ Iteration & Refinement

📋 What the AI Will Do For You

The AI assistant will automatically:

• Create proper folder structures
• Generate agent classes and instructions
• Build custom tools with full functionality
• Set up communication flows
• Create the main agency file
• Test everything to ensure it works

🚀 Manual Alternative (Advanced Users)

If you prefer manual setup, replace the ExampleAgency/ folder with your own agency structure following the Agency Swarm conventions.

Agency Structure Requirements

Your agency must follow this structure:

• Agency Folder: Contains all agents and manifesto
• Agent Folders: Each agent has its own folder with:
• AgentName.py - Agent class definition
• instructions.md - Agent-specific instructions
• tools/ - Folder containing agent tools
• agency_manifesto.md - Shared instructions for all agents

---

🚀 Production Deployment

This repo is compatible with the Agencii platform and standard Agency Swarm deployment patterns, but it is first and foremost a local-first SkillCreatorAgency starter. You can adapt the existing Dockerfile and main.py for your preferred hosting environment.

---

🔨 Development Workflow

🎯 Recommended: AI-Assisted Development

1. Open Cursor IDE with this template
2. Ask the AI: "Create a new agency using the .cursor workflow"
3. Follow the guided process - the AI handles everything automatically
4. Test your agency: python agency.py
5. Deploy to production: Install Agencii GitHub App and push to main

⚙️ Manual Development (Advanced)

If you prefer hands-on development:

1. Create Tools: Build agent tools in tools/ folders
2. Configure Agents: Write instructions.md and agent classes
3. Test Locally: Run python agency.py
4. Deploy: Push to your preferred platform

The .cursor/rules/workflow.mdc file contains the complete development specifications for manual implementation.

---

📚 Key Features

• 🌐 Agencii Cloud Deploy: One-click deployment to Agencii platform
• 🤖 AI-Assisted Creation: Built-in Cursor IDE workflow for automated agency development
• 🔄 Auto-Deploy: Automatic deployment on push to main branch
• 🚀 Ready-to-Deploy: Dockerfile and requirements included
• 🔧 Modular Structure: Easy to customize and extend
• 🛠️ Example Implementation: Complete working example
• 📦 Container Ready: Docker configuration for any platform
• 🔒 Environment Management: Secure API key handling via Agencii dashboard
• 🧪 Local Testing: Terminal demo for development
• 📋 Guided Workflow: 7-step process with AI assistance

---

📖 Learn More

• Agency Swarm Documentation
• Agency Swarm GitHub

---

Credits & Licenses

• This project is licensed under the MIT License (see LICENSE).
• It is based on and inspired by:
• agency-ai-solutions/agency-starter-template
• K-Dense-AI/claude-skills-mcp
• The skill-creator skill under mnt/skills/skill-creator/ is distributed under the Apache 2.0 License (see its LICENSE.txt).

---

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

---

⚡ Quick Tips

• Start Small: Begin with 1-2 agents and expand
• Test Tools: Each tool should work independently
• Clear Instructions: Write detailed agent instructions
• Environment Setup: Always use .env for API keys
• Documentation: Update instructions as you develop

---

Ready to build your AI agency? 🤖✨

🌐 Production Route (Recommended)

1. Sign up at agencii.ai
2. Use this template to create your repository
3. Install Agencii GitHub App
4. Push to main → Automatic deployment!

🛠️ Development Route

Open this template in Cursor IDE and ask the AI to create your agency using the .cursor workflow. The AI will handle everything from setup to testing automatically!

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: AlexFischman
• Source: AlexFischman/mcp-skill-creator-agency
• License: MIT

Install and usage instructions live in the source repository linked above.