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MCP Adr Analysis Server
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MCP Adr Analysis Server

An AI architecture analysis server based on the MCP protocol, providing intelligent architecture decision analysis and ADR management functions for AI assistants, supporting code analysis, security detection, and deployment verification.
Developer toolsArtificial intelligence chatbots#Architecture analysis#AI assistant#Decision record#Code management.TypeScript
2.5 points
4.2K
Open Site

Overview

Installation

Tools List

Content Details

Alternatives

What is the MCP ADR Analysis Server?

This is an intelligent server based on the Model Context Protocol (MCP), specifically designed to provide architecture analysis and decision management functions for AI coding assistants. It can analyze the architecture patterns of codebases, detect technology stacks, generate Architecture Decision Records (ADRs), and provide security checks and test validations. Different from ordinary AI assistants, it directly returns analysis results instead of prompting you to submit analysis requests to other tools.

How to use the MCP ADR Analysis Server?

Simply configure this MCP server in your AI assistant (such as Claude Desktop or Cursor), and then ask questions in natural language to obtain professional architecture analysis. For example, you can ask: 'Analyze the architecture of this React project and suggest improvements.' The server will directly return a detailed analysis report and suggested architecture decisions.

Applicable scenarios

Suitable for development teams, enterprise architects, and users of AI-assisted programming. Particularly applicable to scenarios such as technology selection evaluation for new projects, analysis of existing architecture refactoring, documentation of team decisions, detection of security vulnerabilities, and evaluation of code quality.

Main features

AI intelligent analysis
Integrates OpenRouter.ai to provide instant architecture insights and a 95% confidence score, directly returning analysis results instead of prompts.
Technology stack detection
Automatically identifies the technology stacks, frameworks, and architecture patterns used in a project, supporting multiple programming languages and development frameworks.
ADR decision management
Generates, suggests, and maintains Architecture Decision Records, supporting the automatic creation of ADRs from requirements documents.
Intelligent code association
AI-driven code file discovery, automatically associating ADRs with related code implementations.
Security content masking
Automatically detects and masks sensitive information, protecting keys and private data in the code.
TDD test integration
Supports two-phase test-driven development, including verification and zero-tolerance test blocking.
Deployment readiness check
Verifies whether a project meets deployment requirements, providing hard-blocking checks and repair suggestions.
Enhanced web research
Optional Firecrawl integration provides real-time web research and discovery of best practices.
Advantages
Instant analysis results: Obtain analysis directly in the AI conversation without switching to other tools.
High confidence score: Provides architecture suggestions with 95% confidence, making decisions more reliable.
Seamless integration: Perfectly integrates with mainstream AI assistants (Claude, Cursor, Cline).
Comprehensive coverage: A complete architecture analysis process from technology detection to security review.
Intelligent association: AI-driven association of code and decisions, improving traceability.
Enterprise-level security: Automatically detects and masks sensitive information, complying with security standards.
Limitations
Requires an API key: Some advanced features require an OpenRouter.ai API key.
Learning curve: Initial configuration requires an understanding of the MCP protocol and client settings.
Performance dependence: Analysis of complex projects may take a long time.
Network requirements: Some functions require a stable network connection.
Specific environment: The RHEL system requires a special installation script.

How to use

Install the server
Install the MCP ADR Analysis Server globally via npm.
Get an API key
Visit OpenRouter.ai to obtain an API key to enable the AI analysis function.
Configure environment variables
Set the necessary environment variables, including the API key and execution mode.
Configure the AI client
Add the MCP server settings to the configuration file of your AI assistant (such as Claude Desktop).
Start using
Start the AI assistant and start architecture analysis by asking questions in natural language.

Usage examples

New project architecture evaluation
Evaluate the architecture design of a newly launched React project, providing technology selection suggestions and potential risks.
Security vulnerability detection
Check for security vulnerabilities and risks of sensitive information leakage in the codebase.
Architecture decision documentation
Transform the team's technical decisions into standardized Architecture Decision Records.
Deployment readiness verification
Verify whether a project meets the requirements for deployment in a production environment.

Frequently Asked Questions

What is the difference between the MCP ADR Analysis Server and ordinary AI assistants?
Do I need programming knowledge to use it?
Which AI assistants are supported?
Is the analysis data secure?
How to install it on the RHEL system?
Why does the tool return a prompt instead of a result?

Related resources

GitHub repository
Project source code, issue tracking, and contribution guidelines.
Official documentation
Complete usage guide, tutorials, and API reference.
MCP protocol specification
Official specification and description of the Model Context Protocol.
OpenRouter.ai
Obtain an API key to enable the AI analysis function.
NPM package page
npm installation package information and version history.
Issue feedback
Report bugs, request features, or seek help.

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "adr-analysis": {
      "command": "mcp-adr-analysis-server",
      "env": {
        "PROJECT_PATH": "/path/to/your/project",
        "OPENROUTER_API_KEY": "your_key_here",
        "EXECUTION_MODE": "full"
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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