MCP 服务器

atlas-g-protocol

Resume-as-an-Agent (RAAA) or Portfolio-as-an-Agent (PAAA) allows Agents to talk to your resume, find out if you are available for work, and more. Use the MCP to allow recruiters, managers, and anyone with an agent to "talk" to your resume.

README

Atlas-G Protocol

Agentic Portfolio System - A compliance-grade MCP server that serves as both human and machine-readable portfolio.

🎯 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

🔒 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.txt knowledge graph before responding.

🏗️ Architecture

┌─────────────────────────────────────────────────────┐
│                   Cloud Run Instance                 │
├─────────────────────────────────────────────────────┤
│  ┌─────────────────┐    ┌─────────────────────────┐ │
│  │  React Frontend │◄──►│  FastAPI Backend        │ │
│  │  (Terminal UI)  │    │  - Agent Core           │ │
│  └─────────────────┘    │  - Governance Layer     │ │
│                         │  - MCP Server           │ │
│                         └───────────┬─────────────┘ │
│                                     │               │
│                         ┌───────────▼─────────────┐ │
│                         │  Tools                  │ │
│                         │  - query_resume         │ │
│                         │  - verify_employment    │ │
│                         │  - audit_project        │ │
│                         └─────────────────────────┘ │
└─────────────────────────────────────────────────────┘

🚀 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_KEY

Run Locally

# Start the server
uvicorn backend.main:application --reload --port 8080

# Open http://localhost:8080

Run Tests

pytest backend/tests/ -v

🔧 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
`query_resume`	Semantic search over resume knowledge graph
`verify_employment`	Cross-reference employment claims
`audit_project`	Deep-dive into project architecture

☁️ 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_here

📁 Project Structure

Atlas-G Protocol/
├── backend/
│   ├── __init__.py
│   ├── main.py          # FastAPI application
│   ├── agent.py         # Thought-Action loop
│   ├── governance.py    # Hallucination mitigation
│   ├── mcp_server.py    # FastMCP wrapper
│   ├── config.py        # Settings management
│   └── tools/
│       ├── resume_rag.py
│       └── verification.py
├── frontend/            # React UI (Phase 3)
├── data/
│   └── resume.txt       # Knowledge graph source
├── Dockerfile
├── pyproject.toml
└── mcp_config.json