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Dev Guru

An AI-powered code consultation server that routes programming queries to specific AI models based on requested expertise levels. It enables users to receive structured feedback on debugging, architectural decisions, and code reviews from Gemini, Claude, or GPT.

glama
Updated
Mar 12, 2026
Dev Guru

🧘 Dev Guru

Your AI-powered code consultation MCP server.

Python FastAPI MCP Docker License

When you're stuck, afraid, or just lazy to ask for help — Dev Guru is here.


💡 What is Dev Guru?

Dev Guru is a specialized MCP (Model Context Protocol) server that acts as an on-demand senior code consultant for AI agents. It routes coding problems to the most suitable AI model based on the requested expertise level, providing structured, actionable feedback.

Think of it as a second brain for your AI agent — a guru it can consult when facing tough coding decisions.

🎯 Use Cases

ScenarioHow Dev Guru Helps
🐛 Debugging Complex IssuesYour agent is stuck on a tricky bug. It calls Dev Guru with the context and gets expert-level reasoning and suggestions.
🏗️ Architecture DecisionsUnsure about a design pattern? Dev Guru analyzes your code structure and recommends the best approach.
🔄 Code Review on DemandSubmit code for review and get structured feedback with a thinking process and concrete suggestions.
🤔 Validating ReasoningYour agent has an idea but isn't confident. Dev Guru validates the reasoning and either confirms or corrects the approach.
Multi-Model LeverageAutomatically routes to Gemini, Claude, or GPT based on the complexity level — getting the right model for the right job.

✨ Features

  • 🧠 Expert-based Routing — Automatically selects the best AI model for the task:
    • noviceGemini (fast, efficient)
    • mediumClaude (balanced, analytical)
    • expertOpenAI GPT (deep reasoning)
  • 🔀 OpenRouter Fallback — If a primary API key is missing, seamlessly falls back to OpenRouter
  • 🎛️ Configurable Models — Choose exactly which model to use per level via environment variables
  • FastMCP Core — High-performance MCP server implementation
  • 📦 Skill Management API — Dynamic skill installation and management via REST
  • 🐳 Docker Ready — Multi-stage build with uv for efficient containerized deployments
  • 🧩 Agno Framework — Leverages Agno for agent orchestration and structured outputs

🚀 Quick Start

Prerequisites

  • Python 3.12+
  • uv (recommended)
  • At least one API key: Gemini, Anthropic, OpenAI, or OpenRouter

Installation

# Clone the repository
git clone https://github.com/your-user/dev-guru.git
cd dev-guru

# Create your environment file
cp .env.example .env
# Edit .env with your API keys

# Install dependencies
uv sync

Running

# Start the full API + MCP server
uv run python main.py

Docker

docker compose up --build

⚙️ Configuration

Environment Variables

VariableDescriptionDefault
GEMINI_API_KEYGoogle Gemini API key
ANTHROPIC_API_KEYAnthropic Claude API key
OPENAI_API_KEYOpenAI API key
OPENROUTER_API_KEYOpenRouter API key (universal fallback)
API_KEYOptional API key to protect REST and MCP endpoints
NOVICE_MODELModel ID for novice levelgemini-3.1-pro-preview
MEDIUM_MODELModel ID for medium levelclaude-opus-4.6
ADVANCED_MODELModel ID for expert levelgpt-5.3-codex
PORTServer port8000
DEBUGDebug modetrue

Tip: You only need an OPENROUTER_API_KEY to use all three levels — it acts as a universal fallback for any missing provider key.

🔌 MCP Configuration

Add Dev Guru to your MCP client (Claude Desktop, Cursor, etc.):

{
  "mcpServers": {
    "dev-guru": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/dev-guru",
        "run",
        "python",
        "src/server.py"
      ]
    }
  }
}

📡 API Endpoints

Skill Management

MethodEndpointDescription
GET/skillsList all loaded skills
GET/skills/{name}Get details of a specific skill
POST/skillsInstall a skill (URL or base64 zip)
POST/skills/uploadInstall a skill via file upload
DELETE/skills/{name}Delete a skill

MCP Tool

ToolParametersDescription
call_gurulevel, technologies, context, thinkingConsult the guru about a coding problem

🧪 Testing

PYTHONPATH=. uv run pytest

🏗️ Architecture

graph LR
    A[AI Agent] -->|MCP Protocol| B[Dev Guru Server]
    B -->|novice| C[Gemini]
    B -->|medium| D[Claude]
    B -->|expert| E[GPT-5.3-codex]
    B -.->|fallback| F[OpenRouter]
    F --> C
    F --> D
    F --> E

Built with 🧘 by devs, for devs.

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