Design · MODEL CONTEXT PROTOCOL
sparesparrow mcp project orchestrator
Analyze user input to identify suitable design patterns and project templates. Orchestrate the project, creating initial files from templates.
WHAT IT CONNECTS
What sparesparrow mcp project orchestrator gives an AI Agent
- **Template Management**
- Project templates for quick project setup
- Component templates for modular development
- Variable substitution and validation
- Template discovery and versioning
SECURITY
An MCP listing is not a security review
An MCP server may receive model context, credentials, local files, or permission to call external systems. Review its code, requested environment variables, network behavior, package provenance, and maintenance status before connecting it to an agent.
README
Repository documentation
A comprehensive project orchestration tool for managing Model Context Protocol (MCP) projects, templates, prompts, and Mermaid diagrams.
-
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
The package is not published on PyPI; install it from GitHub:
pip install "git+https://github.com/sparesparrow/mcp-project-orchestrator.git"For AWS integration support:
pip install "mcp-project-orchestrator[aws] @ git+https://github.com/sparesparrow/mcp-project-orchestrator.git"Or, for development, from a clone:
git clone https://github.com/sparesparrow/mcp-project-orchestrator.git
cd mcp-project-orchestrator
pip install -e .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 --helpfrom 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"
})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.shEdit 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
falseto skip generating those components. - Ports and URLs are respected across
.cursor/webhooks,.cursor/agents,DockerfileEXPOSE, andcompose.yaml.
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)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")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
- Clone the repository:
git clone https://github.com/sparesparrow/mcp-project-orchestrator.git
cd mcp-project-orchestrator- Install dependencies:
poetry install- Run tests:
poetry run pytest- Run linting:
poetry run ruff check .
poetry run mypy src/mcp_project_orchestrator- Fork the repository
- Create a feature branch
- Commit your changes
- Push to the branch
- Create a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- Model Context Protocol - The foundation for this project
- Mermaid - For diagram generation
- Poetry - For dependency management
- Ruff - For linting
- mypy - For type checking
Enhanced with OpenSSL project templates and Cursor AI configuration.
mcp-orchestrator create-openssl-project \
--project-name my-secure-app \
--deployment-target fips-governmentmcp-orchestrator deploy-cursor --project-type opensslopenssl-consumer: Standard OpenSSL applicationopenssl-fips: FIPS 140-3 government deployment
COMMUNITY