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DevGuardian MCP Server — v3 Autonomous Engineering Ecosystem

An AI-powered, project-aware coding assistant MCP server built with Gemini 2.0 Flash and UV.
Plug it into Antigravity or Claude Desktop and get a full AI engineering team: debugging, reviewing, testing, deploying, and securing your code — all autonomously.

DevGuardian Demo


What is DevGuardian?

DevGuardian v3 is a multi-agent autonomous engineering ecosystem. It goes far beyond a single script — it reads your entire project structure before acting, uses a team of AI agents to validate work iteratively, and now actively repairs its own CI failures.

Core Design Principles:

  1. Project DNA Awareness — Before writing a single line of code, DevGuardian reads your README, pyproject.toml, full file tree, and import graph. It generates code that fits your architecture, not generic boilerplate.
  2. Agent Swarm with Adversarial Review — A 3-agent pipeline (Coder → Tester → Reviewer) that loops until the code is production-ready. If the Reviewer rejects the code, it sends specific feedback back to the Coder for another pass (up to 3 iterations).
  3. Semantic Memory — DevGuardian remembers your coding style preferences and lessons learned across sessions, stored locally in .devguardian_memory.json.
  4. Sandbox Execution — The Tester agent actually runs the generated code in a safe subprocess to catch runtime errors, not just look for them visually.
  5. Self-Healing CI — If a push to main fails CI checks, a repair job automatically triggers DevGuardian to diagnose and fix the issue, then re-pushes a repair commit.

Tool Reference (31 Tools)

Autonomous Agents

Tool Description
agent_swarm 3-agent pipeline (Coder, Tester, Reviewer) with adversarial feedback loops and sandbox execution. Loops until code is accepted.
autonomous_engineer Stateful LangGraph agent that plans, executes tools in loops, verifies work, and self-corrects.

AI Code Intelligence

Tool Description
debug_error Analyze errors and stack traces; returns root cause and exact fix with full project context.
explain_code Understand what any code does in plain English.
review_code Project-aware code review covering bugs, security, performance, and style.
generate_code Generate clean code tailored to your project's architecture.
improve_code Refactor and improve existing code consistently.

Quality and Testing

Tool Description
test_and_fix TDD Auto-Pilot: generates pytest tests, runs them, fixes source until tests pass.
review_pull_request Fetches PR diffs from GitHub and performs an AI-powered code review.

DevOps and Infrastructure

Tool Description
dockerize Auto-generates Dockerfile and docker-compose.yml tailored to your stack.
generate_ci Auto-generates .github/workflows/ci.yml with linting, testing, Docker, and self-healing jobs.
generate_gitignore Analyzes your project structure and generates a tailored .gitignore. Asks for permission before including .env patterns.

Architecture and Documentation

Tool Description
generate_architecture_map Analyzes internal imports and generates a Mermaid.js dependency diagram of your project.
generate_technical_docs Generates a high-density technical architecture summary using Gemini.

Mass Operations

Tool Description
mass_refactor Applies a single instruction across every Python file in the project simultaneously.

Security

Tool Description
validate_env Validates .env file format safely — never exposes secret values.
security_scan Scans the repo for 20+ credential types and missing .gitignore coverage.

Git Suite

Tool Description
smart_commit AI reads your diff, writes a commit message, scans for credential leaks, then commits.
git_status Show working tree status.
git_add Stage files for commit.
git_commit Commit with a custom message.
git_push Push to remote (protected by the security gate).
git_pull Pull from remote.
git_log View commit history.
git_diff Show staged or unstaged diffs.
git_branch List all branches.
git_checkout Switch or create branches.
git_stash Stash or unstash changes.
git_reset Reset HEAD (soft, mixed, hard).
git_remote List configured remotes.

Setup

Prerequisites

Installation

cd DevGuardian
uv venv
uv pip install -e .

Configure your API key

copy .env.example .env
# Open .env and paste your Gemini API key
# Optionally add GITHUB_TOKEN for private repo PR reviews

Test the server runs

uv run devguardian

You should see no errors — the server waits for MCP connections on stdio.


MCP Configuration

Antigravity (VS Code)

Add to your .gemini/settings.json:

{
  "mcpServers": {
    "devguardian": {
      "command": "uv",
      "args": ["--directory", "C:\\Users\\ASUS\\OneDrive\\Desktop\\DevGuardian", "run", "devguardian"],
      "env": {
        "GEMINI_API_KEY": "your_key_here",
        "GITHUB_TOKEN": "your_github_token_here"
      }
    }
  }
}

Claude Desktop

Add to %APPDATA%\Claude\claude_desktop_config.json:

{
  "mcpServers": {
    "devguardian": {
      "command": "uv",
      "args": ["--directory", "C:\\Users\\ASUS\\OneDrive\\Desktop\\DevGuardian", "run", "devguardian"],
      "env": {
        "GEMINI_API_KEY": "your_key_here"
      }
    }
  }
}

Usage Examples

Agent Swarm — Build a feature with 3 AI agents

"DevGuardian, use the agent swarm to create a rate-limiting utility for our API."
Coder writes a RateLimiter class. Tester finds edge cases. Reviewer rejects and sends feedback. Coder fixes. Reviewer accepts on pass 2. Final production-ready file is returned.

TDD Auto-Pilot — Test-driven bug fixing

"Run test_and_fix on devguardian/tools/debugger.py"
DevGuardian writes pytest tests, runs them, reads the failures, patches the source, and loops until all tests go green.

PR Review — Review any live pull request

"Review PR #42 in myorg/myrepo"
DevGuardian fetches the diff from GitHub and produces a structured review covering bugs, security, performance, and style.

Architecture Map — Visualize your codebase

"Generate an architecture map for this project."
DevGuardian scans all internal imports and produces a Mermaid.js dependency diagram showing how every file connects to every other file.

Smart .gitignore — Context-aware generation

"Generate a gitignore for this project."
DevGuardian reads your tech stack and file structure. It asks for your permission before including .env patterns, then generates a tailored file — not a generic template.

Push Code Safely

"Push my changes to main."
DevGuardian scans all staged files. If it detects a hardcoded API key or token, it blocks the push and reports the exact file and line number.


Project Structure

DevGuardian/
├── .env.example                   Copy to .env and add your API key
├── .gitignore                     Security-focused ignore rules
├── pyproject.toml                 UV project config and dependencies
├── Dockerfile                     Production container
├── docker-compose.yml             Service orchestration
├── README.md
├── tests/
│   └── test_debugger.py           TDD-generated test suite
├── .github/
│   └── workflows/
│       └── ci.yml                 GitHub Actions CI/CD with self-healing job
└── devguardian/
    ├── server.py                  MCP server entry point (31 tools)
    ├── agents/
    │   ├── engineer.py            Stateful LangGraph autonomous agent
    │   └── swarm.py               3-Agent Swarm v3 with adversarial loops
    ├── tools/
    │   ├── debugger.py            debug_error
    │   ├── code_helper.py         explain, review, generate, improve
    │   ├── git_ops.py             Full git suite + smart_commit
    │   ├── tdd.py                 TDD Auto-Pilot
    │   ├── github_review.py       GitHub PR Reviewer
    │   ├── infra.py               Dockerfile, CI/CD, and gitignore generators
    │   ├── architect.py           Architecture mapping and technical docs
    │   ├── self_healing.py        CI failure detection and repair engine
    │   └── mass_refactor.py       Mass codebase refactoring
    └── utils/
        ├── gemini_client.py       Gemini 2.0 Flash wrapper
        ├── file_reader.py         Project DNA context builder
        ├── security.py            Pre-push security gate and .env validator
        ├── memory.py              Persistent semantic memory (JSON-based)
        └── executor.py            Safe subprocess execution sandbox

Security Model

  • Anti-Leak Shield: security.py detects 20+ credential types (AWS, GitHub, OpenAI, Google, Stripe, Slack) before any git push or smart_commit.
  • Precise Detection: Only flags hardcoded quoted values — no false positives on os.getenv() calls.
  • Env Safety: validate_env reviews your .env file structure — shows keys but never exposes values.
  • Permission-Based Gitignore: The generate_gitignore tool asks for explicit user permission before adding .env patterns — nothing is done without your approval.
  • Local Execution: Your code never leaves your machine except for Gemini API calls.

CI/CD Pipeline

The pipeline runs on every push and pull request to main:

  1. lint — Ruff checks code style and format
  2. test — Pytest runs the full test suite with coverage
  3. Self-Healing Repair — Triggers only if lint or test fails. Uses the Agent Swarm to diagnose, fix, and re-push a repair commit automatically.
  4. build — Builds the Python package
  5. docker — Builds the Docker image

Docker

docker compose up --build

Built by Karan using Gemini 2.0 Flash, LangGraph, MCP SDK, and UV.

About

An AI-powered, Project-Aware coding assistant MCP server built with Gemini 2.0 Flash and UV. Plug it into Antigravity or Claude Desktop for AI-assisted coding, debugging, and robust Git operations — now with a built-in Pre-Push Security Gate.

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