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mentor-mcp-server

mentor-mcp-server

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github.com/cyanheadsDeveloper Tools32Updated 91w ago

About mentor-mcp-server

mentor-mcp-server is an MCP server that gives LLM agents a second opinion by calling the Deepseek-Reasoner (R1) model through the Deepseek API. It targets developers and agents that need code review, design critique, writing feedback or brainstorming.

Key features

  1. 01Code review with security and performance suggestions
  2. 02UI/UX and architecture design critique
  3. 03Writing and documentation feedback
  4. 04Feature enhancement brainstorming
  5. 05Configurable model, token limit, retries and timeout

Use cases

  1. 01Having an agent review a TypeScript file before commit
  2. 02Requesting a second opinion on a UI or architecture design
  3. 03Improving the structure and clarity of technical documentation

MCP support

This project is an MCP server that provides tools such as code_review, design_critique, writing_feedback and brainstorm_enhancements to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

mentor-mcp-server

TypeScript Model Context Protocol Version License Status GitHub

A Model Context Protocol server providing LLM Agents a second opinion via AI-powered Deepseek-Reasoning (R1) mentorship capabilities, including code review, design critique, writing feedback, and idea brainstorming through the Deepseek API. Set your LLM Agent up for success with expert second opinions and actionable insights.

Model Context Protocol

The Model Context Protocol (MCP) enables communication between:

  • Clients: Claude Desktop, IDEs, and other MCP-compatible clients
  • Servers: Tools and resources for task management and automation
  • LLM Agents: AI models that leverage the server's capabilities

Table of Contents

Features

Code Analysis
  • Comprehensive code reviews
  • Bug detection and prevention
  • Style and best practices evaluation
  • Performance optimization suggestions
  • Security vulnerability assessment
Design & Architecture
  • UI/UX design critiques
  • Architectural diagram analysis
  • Design pattern recommendations
  • Accessibility evaluation
  • Consistency checks
Content Enhancement
  • Writing feedback and improvement
  • Grammar and style analysis
  • Documentation review
  • Content clarity assessment
  • Structural recommendations
Strategic Planning
  • Feature enhancement brainstorming
  • Second opinions on approaches
  • Innovation suggestions
  • Feasibility analysis
  • User value assessment

Installation

# Clone the repository
git clone [email protected]:cyanheads/mentor-mcp-server.git
cd mentor-mcp-server

# Install dependencies
npm install

# Build the project
npm run build

Configuration

Add to your MCP client settings:

{
  "mcpServers": {
    "mentor": {
      "command": "node",
      "args": ["build/index.js"],
      "env": {
        "DEEPSEEK_API_KEY": "your_api_key",
        "DEEPSEEK_MODEL": "deepseek-reasoner",
        "DEEPSEEK_MAX_TOKENS": "8192",
        "DEEPSEEK_MAX_RETRIES": "3",
        "DEEPSEEK_TIMEOUT": "30000"
      }
    }
  }
}
Environment Variables
VariableRequiredDefaultDescription
DEEPSEEK_API_KEYYes-Your Deepseek API key
DEEPSEEK_MODELYesdeepseek-reasonerDeepseek model name
DEEPSEEK_MAX_TOKENSNo8192Maximum tokens per request
DEEPSEEK_MAX_RETRIESNo3Number of retry attempts
DEEPSEEK_TIMEOUTNo30000Request timeout (ms)

Tools

Code Review
<use_mcp_tool>
<server_name>mentor-mcp-server</server_name>
<tool_name>code_review</tool_name>
<arguments>
{
  "file_path": "src/app.ts",
  "language": "typescript"
}
</arguments>
</use_mcp_tool>
Design Critique
<use_mcp_tool>
<server_name>mentor-mcp-server</server_name>
<tool_name>design_critique</tool_name>
<arguments>
{
  "design_document": "path/to/design.fig",
  "design_type": "web UI"
}
</arguments>
</use_mcp_tool>
Writing Feedback
<use_mcp_tool>
<server_name>mentor-mcp-server</server_name>
<tool_name>writing_feedback</tool_name>
<arguments>
{
  "text": "Documentation content...",
  "writing_type": "documentation"
}
</arguments>
</use_mcp_tool>
Feature Enhancement
<use_mcp_tool>
<server_name>mentor-mcp-server</server_name>
<tool_name>brainstorm_enhancements</tool_name>
<arguments>
{
  "concept": "User authentication system"
}
</arguments>
</use_mcp_tool>

Examples

Detailed examples of each tool's usage and output can be found in the examples directory:

Each example includes the request format and sample response, demonstrating the tool's capabilities and output structure.

Development

# Build TypeScript code
npm run build

# Start the server
npm run start

# Development with watch mode
npm run dev

# Clean build artifacts
npm run clean

Project Structure

src/
├── api/         # API integration modules
├── tools/       # Tool implementations
│   ├── second-opinion/
│   ├── code-review/
│   ├── design-critique/
│   ├── writing-feedback/
│   └── brainstorm-enhancements/
├── types/       # TypeScript type definitions
├── utils/       # Utility functions
├── config.ts    # Server configuration
├── index.ts     # Entry point
└── server.ts    # Main server implementation

License

Apache License 2.0. See LICENSE for more information.


Built with the Model Context Protocol

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.