Skip to main content

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:

  1. Code Ingestion: The system analyzes your codebase, parsing files and understanding their structure.
  2. Embedding Generation: Code, documentation, and architectural decisions are converted into vector embeddings.
  3. Vector Storage: These embeddings are stored in a Qdrant vector database, enabling semantic search and relationship mapping.
  4. Contextual Analysis: When queried, the system retrieves relevant context from the vector database and applies specialized models to generate insights.
  5. Action Generation: Based on analysis, the system can recommend actions, generate documentation, or provide debugging assistance.

System Architecture

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

# Install the package
pip install mcp-codebase-insight

# Set up basic environment variables
export MCP_HOST=127.0.0.1
export MCP_PORT=3000
export QDRANT_URL=http://localhost:6333
export MCP_DOCS_CACHE_DIR=./docs
export MCP_ADR_DIR=./docs/adrs
export MCP_KB_STORAGE_DIR=./knowledge
export MCP_DISK_CACHE_DIR=./cache

# Start the server
mcp-codebase-insight --host 127.0.0.1 --port 3000 --log-level INFO

Note: For a complete list of environment variables and configuration options, see the Configuration Guide.

Using Docker

docker run -p 3000:3000 \
    --env-file .env \
    -v $(pwd)/docs:/app/docs \
    -v $(pwd)/knowledge:/app/knowledge \
    tosin2013/mcp-codebase-insight

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

Metadata

Release files for mcp-codebase-insight 0.2.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mcp-codebase-insight 0.2.2
File Size Uploaded Provenance
mcp_codebase_insight-0.2.2.tar.gz 55.8 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for mcp-codebase-insight 0.2.2
File Interpreter ABI Platform
mcp_codebase_insight-0.2.2-py3-none-any.whl Python 3 none any Details

Total release size: 114.1 kB

Release files / mcp_codebase_insight-0.2.2.tar.gz

Download URL mcp_codebase_insight-0.2.2.tar.gz
Size 55.8 kB
Tags Source
SHA-256 checksum
How to use checksums
ab63d5829b24d69ba8efc36b5288295db48d75def679a64a5a79322681f7b854
BLAKE2b-256 checksum
How to use checksums
80f678bfd4d704e48689472c19888b1edbf43bee8985e3b541b960aa5b841222
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.2

Release files / mcp_codebase_insight-0.2.2-py3-none-any.whl

Download URL mcp_codebase_insight-0.2.2-py3-none-any.whl
Size 58.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
29a568655bdc3626397c3bed31e39e2e6e78ae8ead09bfc9ecc8d0f1b9467016
BLAKE2b-256 checksum
How to use checksums
66f907867f847b8acf1a7418ec41711ef6110070c541d5eac93734dcb3c3e3a2
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.2

Security for mcp-codebase-insight 0.2.2

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page