MCP Codebase Insight
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
Integrations
Enables configuration of the MCP server through environment variables loaded from .env files, simplifying deployment setup and configuration management.
Provides containerized deployment of the MCP Codebase Insight server with support for environment variables and volume mounting for persistent storage of documentation, knowledge, and cache data.
Offers integration for issue tracking and community discussions through GitHub repositories, supporting user feedback and problem resolution workflows.
MCP Codebase Insight
MCP Codebase Insight is a server component of the Model Context Protocol (MCP) that provides intelligent analysis and insights into codebases. It uses vector search and machine learning to understand code patterns, architectural decisions, and documentation.
Target Audience
MCP Codebase Insight is designed primarily for:
- Software Developers: Who want AI-assisted code analysis and improvements
- Software Architects: Managing architecture decisions and technical documentation
- DevOps Engineers: Monitoring system health and integrating with CI/CD pipelines
- Technical Leads: Ensuring best practices and maintaining knowledge management
- Data Scientists: Who can leverage the system for code pattern analysis
This tool is most valuable for teams working on complex codebases that require consistent patterns, architectural oversight, and thorough documentation.
Features
- Code Analysis: Identify patterns, vulnerabilities, and optimization opportunities
- ADR Management: Track architectural decisions with context
- Documentation: Auto-generate and maintain technical documentation
- Knowledge Base: Store reusable code patterns and solutions
- Debug System: Analyze and fix issues with context awareness
- Build Verification: Automated end-to-end build verification
How It Works
MCP Codebase Insight operates through a pipeline of intelligent analysis:
- Code Ingestion: The system analyzes your codebase, parsing files and understanding their structure.
- Embedding Generation: Code, documentation, and architectural decisions are converted into vector embeddings.
- Vector Storage: These embeddings are stored in a Qdrant vector database, enabling semantic search and relationship mapping.
- Contextual Analysis: When queried, the system retrieves relevant context from the vector database and applies specialized models to generate insights.
- Action Generation: Based on analysis, the system can recommend actions, generate documentation, or provide debugging assistance.
Note: The above URL is a placeholder for an architecture diagram. Replace with an actual diagram path.
Quick Start
For detailed installation and usage instructions, please refer to our documentation.
Important Requirement: MCP Codebase Insight requires a running Qdrant vector database instance to function properly. See Qdrant Setup for installation instructions.
Basic Installation
Note: For a complete list of environment variables and configuration options, see the Configuration Guide.
Using Docker
Documentation
For complete documentation, please see the docs directory:
License
This project is licensed under the MIT License - see the LICENSE file for details.
Support
This server cannot be installed
A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.