System Architect Scaffolder

A robust utility suite engineered for governing Model Context Protocol (MCP) assets, encompassing boilerplate structures, instructional directives, and Mermaid visual representations.

Core Capabilities

• Boilerplate Asset Administration
• Predefined structures for accelerated project commencement
• Modular component schematics for incremental construction
• Parameter injection and integrity checking

• Asset cataloging and version tracking

• Directive Template Governance

• System-level and user-facing prompt formats
• Dynamic variable insertion
• Categorization and revision control for directives

• Simplified retrieval and reusability of prompts

• Mermaid Visualization Engineering

• Construction of operational flowcharts
• Generation of interaction sequence charts
• Creation of structural class diagrams
• Output rendering in SVG and PNG formats

• Schematic correctness verification

• Cloud Infrastructure Alignment (AWS MCP)

• Facilitated access to Amazon Web Services primitives (S3, EC2, Lambda, CloudFormation, IAM)
• Adherence enforcement for AWS operational best practices
• Suggestions for expenditure minimization
• Security posture and regulatory compliance guidance
• Refer to AWS_MCP.md for comprehensive specifics

Deployment Instructions

bash pip install mcp-project-orchestrator

For functionality integrating with AWS services:

bash pip install mcp-project-orchestrator[aws]

Using Poetry:

bash poetry add mcp-project-orchestrator

Or with AWS enablement

poetry add mcp-project-orchestrator -E aws

Utilizing as a Conan Dependency (for ai-servis)

This repository furnishes a Conan v2 package that exposes the Python runtime environment and the command-line interface. Within the ai-servis's conanfile.py, incorporate:

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

Subsequently, activate the execution environment to place mcp-orchestrator onto the system PATH and the package onto PYTHONPATH:

bash 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

Initial Configuration Guide

Project Scaffolding Assets

python from mcp_project_orchestrator.templates import TemplateManager

Instantiate the template administration utility

manager = TemplateManager("path/to/templates")

Retrieve the catalog of accessible templates

templates = manager.list_templates() print(templates)

Deploy a chosen project structure template

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

Configuration-Driven Initiative Orchestration

The initialization script consumes settings from config/project_orchestration.json to selectively activate/deactivate functionalities and define operational parameters like network ports and tool settings.

Execute the setup routine:

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

Modify config/project_orchestration.json to govern the structure generation process:

{ "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 } }

• Designate entries as false to suppress the generation of corresponding elements.
• Network ingress/egress points and URI references are observed across .cursor/webhooks, .cursor/agents, Dockerfile's EXPOSE directive, and compose.yaml.

Directive Administration

python from mcp_project_orchestrator.prompts import PromptManager

Instantiate the directive management utility

manager = PromptManager("path/to/prompts")

Obtain the manifest of accessible directives

prompts = manager.list_prompts() print(prompts)

Synthesize a directive using provided parameters

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

Diagramming with Mermaid

python from mcp_project_orchestrator.mermaid import MermaidGenerator, MermaidRenderer

Initialize the generation modules

generator = MermaidGenerator() renderer = MermaidRenderer()

Construct a process flowchart

flowchart = generator.generate_flowchart( nodes=[ ("A", "Initiation"), ("B", "Execution Phase"), ("C", "Conclusion") ], edges=[ ("A", "B", "Transition"), ("B", "C", "Completion Signal") ] )

Output the schematic as SVG

renderer.render(flowchart, "flowchart.svg")

Repository Layout

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

Engineering Practices

1. Repository acquisition: bash git clone https://github.com/yourusername/mcp-project-orchestrator.git cd mcp-project-orchestrator

2. Installing development dependencies: bash poetry install

3. Executing unit and integration verification: bash poetry run pytest

4. Running code quality checks: bash poetry run ruff check . poetry run mypy src/mcp_project_orchestrator

Collaborative Contributions

1. Branch off the main repository (Fork)
2. Establish a dedicated feature branch
3. Commit requisite modifications
4. Push changes to your branch
5. Initiate a Merge/Pull Request

Licensing Terms

This software is governed by the stipulations of the MIT License; consult the LICENSE documentation for full particulars.

Recognition

• Model Context Protocol - The foundational framework underpinning this utility
• Mermaid - The engine for visual diagram construction
• Poetry - For managing project dependencies
• Ruff - For source code static analysis
• mypy - For static type verification