logo
Free, unlimited AI code reviews that run on commit
git-lrc git-lrc GitHub Install Now We'd appreciate a star git-lrc - Free, unlimited AI code reviews that run on commit | Product Hunt git-lrc - Free, unlimited AI code reviews that run on commit | Product Hunt

mcp-project-orchestrator

Streamlines software project setup using standardized templates and best practices, automatically generating comprehensive documentation and visual diagrams to enhance project architecture and implementation strategy.

Author

mcp-project-orchestrator logo

sparesparrow

MIT License

Quick Info

GitHub GitHub Stars 15
NPM Weekly Downloads 0
Tools 1
Last Updated 2026-02-19

Tags

devopsdocumentationdiagramsdevops cicdproject orchestratorproject architecture

MCP Project Orchestrator

codecov PyPI version Python 3.9+ License: MIT

A comprehensive project orchestration tool for managing Model Context Protocol (MCP) projects, templates, prompts, and Mermaid diagrams.

Features

  • Template Management
  • Project templates for quick project setup
  • Component templates for modular development
  • Variable substitution and validation
  • Template discovery and versioning

  • Prompt Management

  • System and user prompt templates
  • Variable substitution
  • Prompt categorization and versioning
  • Easy prompt discovery and reuse

  • Mermaid Diagram Generation

  • Flowchart generation
  • Sequence diagram generation
  • Class diagram generation
  • SVG and PNG rendering
  • Diagram validation

  • AWS MCP Integration

  • AWS service access (S3, EC2, Lambda, CloudFormation, IAM)
  • AWS best practices enforcement
  • Cost optimization recommendations
  • Security and compliance guidance
  • See AWS_MCP.md for details

Installation

pip install mcp-project-orchestrator

For AWS integration support:

pip install mcp-project-orchestrator[aws]

Or with Poetry:

poetry add mcp-project-orchestrator
# Or with AWS support
poetry add mcp-project-orchestrator -E aws

Using as a Conan dependency (for ai-servis)

This repository provides a Conan v2 package exposing the Python environment and CLI. In ai-servis's conanfile.py add:

def requirements(self):
    self.requires("mcp-project-orchestrator/0.1.0@sparesparrow/stable")

Then activate the run environment so mcp-orchestrator is on PATH and the package is on PYTHONPATH:

conan profile detect --force
conan create . --user=sparesparrow --channel=stable
conan install mcp-project-orchestrator/0.1.0@sparesparrow/stable -g VirtualRunEnv
./conanrun.sh mcp-orchestrator --help

Quick Start

Project Templates

from mcp_project_orchestrator.templates import TemplateManager

# Initialize template manager
manager = TemplateManager("path/to/templates")

# List available templates
templates = manager.list_templates()
print(templates)

# Apply a project template
manager.apply_template("fastapi-project", {
    "project_name": "my-api",
    "project_description": "My FastAPI project",
    "author_name": "John Doe",
    "author_email": "john@example.com"
})

JSON-Driven Project Orchestration

The setup script reads config/project_orchestration.json to enable/disable features and set ports and tool options.

Run the setup:

chmod +x scripts/setup_orchestrator.sh
scripts/setup_orchestrator.sh

Edit config/project_orchestration.json to control scaffolding:

{
  "enable": {
    "cursorConfigs": true,
    "pythonMcp": true,
    "tsMcp": true,
    "cppMcp": true,
    "mcpClient": true,
    "backgroundAgent": true,
    "githubActions": true,
    "devcontainer": true,
    "awsTerraform": true,
    "webAndMcp": true,
    "cppConan": true,
    "esp32": true,
    "android": true
  }
}
  • Set items to false to skip generating those components.
  • Ports and URLs are respected across .cursor/webhooks, .cursor/agents, Dockerfile EXPOSE, and compose.yaml.

Prompt Management

from mcp_project_orchestrator.prompts import PromptManager

# Initialize prompt manager
manager = PromptManager("path/to/prompts")

# List available prompts
prompts = manager.list_prompts()
print(prompts)

# Render a prompt with variables
rendered = manager.render_prompt("system-prompt", {
    "name": "User",
    "project": "MCP"
})
print(rendered)

Mermaid Diagrams

from mcp_project_orchestrator.mermaid import MermaidGenerator, MermaidRenderer

# Initialize generators
generator = MermaidGenerator()
renderer = MermaidRenderer()

# Generate a flowchart
flowchart = generator.generate_flowchart(
    nodes=[
        ("A", "Start"),
        ("B", "Process"),
        ("C", "End")
    ],
    edges=[
        ("A", "B", ""),
        ("B", "C", "")
    ]
)

# Render to SVG
renderer.render(flowchart, "flowchart.svg")

Project Structure

mcp-project-orchestrator/
├── src/
│   └── mcp_project_orchestrator/
│       ├── templates/
│       │   ├── __init__.py
│       │   ├── base.py
│       │   ├── project.py
│       │   ├── component.py
│       │   └── manager.py
│       ├── prompts/
│       │   ├── __init__.py
│       │   ├── template.py
│       │   └── manager.py
│       └── mermaid/
│           ├── __init__.py
│           ├── generator.py
│           └── renderer.py
├── tests/
│   ├── __init__.py
│   ├── conftest.py
│   ├── test_templates.py
│   ├── test_prompts.py
│   └── test_mermaid.py
├── docs/
├── examples/
├── .github/
│   └── workflows/
│       └── ci.yml
├── pyproject.toml
├── Containerfile
└── README.md

Development

  1. Clone the repository:
git clone https://github.com/yourusername/mcp-project-orchestrator.git
cd mcp-project-orchestrator
  1. Install dependencies:
poetry install
  1. Run tests:
poetry run pytest
  1. Run linting:
poetry run ruff check .
poetry run mypy src/mcp_project_orchestrator

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Commit your changes
  4. Push to the branch
  5. Create a Pull Request

License

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

Acknowledgments

See Also

`