Atlas-G Protocol
Agentic Portfolio System - A compliance-grade MCP server that serves as both human and machine-readable portfolio.
šÆ Overview
Atlas-G Protocol transforms a traditional developer portfolio into an autonomous agent that demonstrates compliance-grade engineering in real-time. Instead of reading about experience with "strict state management" and "hallucination mitigation," users interact with an agent that actively demonstrates these capabilities.
Key Features
MCP Server: Machine-readable portfolio accessible by AI development environments
Governance Layer: Real-time hallucination mitigation via knowledge graph validation
Live Audit Log: Streams internal compliance checks to the UI
WebSocket Streaming: Real-time "Thought-Action" loop visualization
CSP Headers: Configured for DEV.to iframe embedding
š Privacy & Data Governance
The Atlas-G Protocol follows a "Private-by-Design" pattern to ensure sensitive career data isn't leaked in public repositories:
Template Pattern: All proprietary information (work history, PII) is stored in
data/resume.txt, which is explicitly excluded from the repository via.gitignore.resume.template.txt: A sanitized template is provided for open-source users to populate with their own data.
Hallucination Mitigation: The agent's governance layer validates every claim against the local
resume.txtknowledge graph before responding.
šļø Architecture
āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā
ā Cloud Run Instance ā
āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāā¤
ā āāāāāāāāāāāāāāāāāāā āāāāāāāāāāāāāāāāāāāāāāāāāāā ā
ā ā React Frontend āāāāāŗā FastAPI Backend ā ā
ā ā (Terminal UI) ā ā - Agent Core ā ā
ā āāāāāāāāāāāāāāāāāāā ā - Governance Layer ā ā
ā ā - MCP Server ā ā
ā āāāāāāāāāāāāā¬āāāāāāāāāāāāāā ā
ā ā ā
ā āāāāāāāāāāāāā¼āāāāāāāāāāāāāā ā
ā ā Tools ā ā
ā ā - query_resume ā ā
ā ā - verify_employment ā ā
ā ā - audit_project ā ā
ā āāāāāāāāāāāāāāāāāāāāāāāāāāā ā
āāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāāš Quick Start
Prerequisites
Python 3.11+
Google Cloud API Key (for Gemini)
Installation
# Clone the repository
cd Atlas-G\ Protocol
# Create virtual environment
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
# Install dependencies
pip install -e ".[dev]"
# Copy environment template
cp .env.example .env
# Edit .env with your GOOGLE_API_KEYRun Locally
# Start the server
uvicorn backend.main:application --reload --port 8080
# Open http://localhost:8080Run Tests
pytest backend/tests/ -vš§ MCP Integration
Connect your AI development environment to the Atlas-G MCP server:
{
"mcpServers": {
"atlas-g-protocol": {
"command": "python",
"args": ["-m", "backend.mcp_server"]
}
}
}Available Tools
Tool | Description |
| Semantic search over resume knowledge graph |
| Cross-reference employment claims |
| Deep-dive into project architecture |
āļø Deploy to Cloud Run
gcloud run deploy atlas-g-portfolio \
--source . \
--allow-unauthenticated \
--region us-central1 \
--labels dev-tutorial=devnewyear2026 \
--set-env-vars GOOGLE_API_KEY=your_key_hereš Project Structure
Atlas-G Protocol/
āāā backend/
ā āāā __init__.py
ā āāā main.py # FastAPI application
ā āāā agent.py # Thought-Action loop
ā āāā governance.py # Hallucination mitigation
ā āāā mcp_server.py # FastMCP wrapper
ā āāā config.py # Settings management
ā āāā tools/
ā āāā resume_rag.py
ā āāā verification.py
āāā frontend/ # React UI (Phase 3)
āāā data/
ā āāā resume.txt # Knowledge graph source
āāā Dockerfile
āāā pyproject.toml
āāā mcp_config.jsonš Security
CSP Headers:
frame-ancestors 'self' https://dev.to https://*.dev.toGovernance Layer: All AI responses validated against resume data
PII Detection: Automatic filtering of sensitive information
Jailbreak Protection: Pattern-based detection and blocking
š License
MIT License - See LICENSE for details.
š¢ Credits
Audio: Emergency Alarm.wav by Mozfoo (CC0)