Repository Intelligence

Lyra Intel

Complete Intelligence Infrastructure Engine for Massive-Scale Codebase Analysis

📚 [Full Documentation](docs/README.md) | Quick Start | Use Cases | API Reference

Analyze codebases 10-100x faster with AI-powered insights, security scanning, and semantic search.

⚡ Active Development

Lyra Intel is actively being enhanced with improvements daily. The core platform is production-ready and being used in enterprise deployments. Thank you for your contributions! 🙌

Why Lyra Intel?

Most code analysis tools force a choice: automation at the cost of understanding, or manual inspection with no scale.

Lyra Intel is built on a different principle: Give developers and security teams the intelligence they need to make informed decisions at scale.

You get:

• ✅ Complete visibility - Understand your entire codebase, not just highlighted issues
• ✅ AI-powered insights - Get context and explanations, not just lists of problems
• ✅ Security you control - Run locally or in your cloud, with no data leaving your infrastructure
• ✅ Scale without sacrifice - Analyze 1 million lines or 1 billion lines with the same ease
• ✅ Open source - Full transparency, no vendor lock-in, customize for your needs

Perfect for teams that want to own their code intelligence.

What is Lyra Intel?

Lyra Intel is a comprehensive, production-ready intelligence platform designed to understand, secure, and improve codebases of any size - from small projects to enterprise monorepos with millions of lines of code.

Unlike traditional linters or SonarQube-style tools, Lyra Intel combines:

• Deep code analysis (AST parsing, dependency graphs, complexity metrics)
• AI-powered insights (OpenAI, Anthropic, or local models)
• Semantic code search (ML-powered search beyond keywords)
• Security scanning (secrets, OWASP, CVE detection)
• Knowledge graphs (understand relationships in your code)
• Forensic analysis (find dead code, document gaps, technical debt)

Why You Need Lyra Intel

For Security Teams:

• Automatically find hardcoded secrets, SQL injection risks, OWASP vulnerabilities
• Track security across massive codebases without manual scanning
• Generate compliance reports (SOC2, HIPAA, PCI-DSS ready)

For Development Teams:

• Understand unfamiliar codebases in hours, not weeks
• Find dead code and technical debt before they become problems
• Make data-driven architectural decisions
• Detect complex bugs that static analysis misses

For Engineering Leaders:

• Quantify code quality and technical debt
• Track metrics across teams and projects
• Plan migrations and upgrades with confidence
• Reduce time spent on code reviews

What You Can Do

With 70+ specialized components, Lyra Intel enables:

See real-world use cases →

🚀 Features

Lyra Intel includes 70+ specialized components organized by capability:

View All Features (70+ Components)

Core Analysis - Understand Your Code

• 📁 File Crawler - Parallel directory traversal with streaming for memory efficiency. Process millions of files without memory issues.
• 📜 Git Collector - Complete commit history, blame analysis, contributor stats. Understand who changed what and when.
• 🔍 AST Analyzer - Multi-language syntax tree parsing (Python, JS/TS, Go, Rust, Java, C++, C#, Ruby, PHP). Get accurate code structure.
• 🔗 Dependency Mapper - Build complete dependency graphs with circular detection. Understand your architecture.
• ⚠️ Pattern Detector - Find code smells, anti-patterns, security issues. Detect problems before they become expensive.

Scalability - From Laptop to Enterprise

• 🖥️ Local Mode - Single machine analysis for development. No setup needed, runs instantly on your machine.
• 🌐 Distributed Mode - Multi-worker processing for larger codebases. Scale analysis to 100K+ files efficiently.
• ☁️ Cloud Massive Mode - Auto-scaling cloud infrastructure (AWS, GCP, Azure). Analyze monorepos with millions of files.

Storage Options - Flexibility for Any Scale

• SQLite - Local development and small projects. Built-in, no dependencies.
• PostgreSQL - Production deployments. Reliable, proven, scalable.
• BigQuery - Massive-scale analytics. Query 1M+ analysis results instantly.
• Cache Layer - Memory, File, Redis backends with TTL/LRU eviction. Speed up repeated analyses.

🔐 Security - Find Vulnerabilities Before They Become Breaches

• Security Scanner - OWASP Top 10, hardcoded secrets, SQL injection detection. Scan 50+ vulnerability patterns.
• Vulnerability Database - Track known CVEs and advisories. Stay updated on emerging threats.
• Custom Rules - Define custom security patterns. Enforce your organization's security standards.

🤖 AI Integration - Get Smarter Insights

• AI Analyzer - Code explanation, bug detection, refactoring suggestions. Understand complex code instantly.
• Multiple Providers - OpenAI (GPT-4/3.5), Anthropic (Claude), or Local (Ollama/llama.cpp). Choose what fits your workflow.
• Cost Effective - Local models for free analysis, or cloud models for maximum accuracy.

📊 Visualization & Reports - Communicate Results

• Graph Generator - Export to D3.js, Mermaid, Graphviz DOT. Visualize dependencies and architecture.
• Report Generator - Executive, Technical, Security, Architecture reports. Different reports for different audiences.
• Web Dashboard - Interactive D3.js/Cytoscape visualization. Explore your codebase visually.

🌐 API & Enterprise Features

• REST API Server - 15+ endpoints for integration. Build on top of Lyra Intel.
• Authentication - API Key, JWT, OAuth 2.0 (SSO), LDAP support. Secure access control.
• RBAC - Role-based access control. Manage permissions across your team.
• Rate Limiting - Protect your infrastructure. Scale safely.

🔬 Forensic Analysis - Find Hidden Problems

• Forensic Analyzer - Code↔doc bidirectional mapping. Find documentation gaps automatically.
• Dead Code Detector - Find unused functions, classes, imports. Clean up your codebase.
• Complexity Analyzer - Cyclomatic, Cognitive, Halstead metrics. Identify problematic code.

📋 More Capabilities

• Code Generation - AI-powered function/class/API generation with custom templates
• Diff & Impact Analysis - Understand what changed and why it matters
• Migration Planning - Plan framework/version upgrades with step-by-step guidance
• Code Profiling - Detect N+1 queries, blocking I/O, inefficient algorithms
• Schema Analysis - Database schema analysis from ORM models
• Documentation Generator - Auto-generate API docs and changelogs
• Workflow Engine - Define and execute multi-step analysis pipelines

🔍 Auto-Discovery Pipeline (NEW)

• GitHub Scanner - Automatically discover new MCP crypto tools from GitHub
• AI Tool Analyzer - Extract tool definitions using AI/pattern matching
• Security Scanner - Scan discovered tools for vulnerabilities
• Registry Submitter - Submit approved tools to the Lyra Registry
• Daily Automation - GitHub Actions workflow for continuous discovery

See Discovery Documentation →

📚 Complete Documentation

Lyra Intel includes comprehensive documentation covering every aspect of the platform:

Core Documentation

• [📖 FEATURES.md](docs/FEATURES.md) - Detailed feature documentation with code examples for:
• Semantic Search (ML-powered code search)
• SSO Integration (OAuth 2.0, SAML 2.0, LDAP)
• Language Parsers (C++, C#, Ruby, PHP)
• Plugin System
• IDE Extensions (VS Code, JetBrains)
• CI/CD Integrations (GitLab, Bitbucket, GitHub Actions)
• Export Formats (PDF, SARIF, Excel, CSV)
• WebSocket Streaming
• Interactive CLI
• Web Dashboard
• Monitoring & Metrics (Prometheus, Grafana)

• [💻 EXAMPLES.md](docs/EXAMPLES.md) - Working code examples for:
• Quick start (60-second analysis)
• Core analysis workflows
• Semantic search usage
• SSO setup and configuration
• Language-specific parsing
• Custom plugin development
• IDE extension installation
• CI/CD pipeline integration
• Real-time WebSocket streaming
• Monitoring setup
• Complete end-to-end workflows

• [🏗️ ARCHITECTURE.md](docs/ARCHITECTURE.md) - Technical architecture documentation:
• System overview and design
• Core component architecture
• Data flow diagrams
• Module organization
• Extension points
• Deployment architectures (single server, Kubernetes, AWS)
• Performance & scalability
• Security architecture
• Technology stack

• [🔌 API.md](docs/API.md) - Complete REST API reference
• [🚀 DEPLOYMENT.md](docs/DEPLOYMENT.md) - Deployment guides (Docker, Kubernetes, AWS)
• [📜 openapi.yaml](docs/openapi.yaml) - OpenAPI 3.0 specification

Real-World Workflows

• [💼 USE_CASES.md](docs/USE_CASES.md) - Practical workflows and best practices:
• Securing legacy codebases
• Pre-commit code quality gates
• CI/CD security pipelines
• Code review assistance
• Monorepo migration planning
• Technical debt tracking
• Building team knowledge bases
• Integration patterns
• Performance optimization tips

Getting Started Guides

• [⚡ QUICKSTART.md](QUICKSTART.md) - Get up and running in 5 minutes
• [🔧 INSTALL.md](INSTALL.md) - Installation instructions
• [📚 TUTORIAL.md](docs/TUTORIAL.md) - Step-by-step tutorials for common use cases:
• First analysis
• Security audit
• Semantic search setup
• CI/CD integration
• Custom plugin development
• Production deployment
• Real-time dashboard
• [❓ FAQ.md](docs/FAQ.md) - Frequently asked questions
• [🤝 CONTRIBUTING.md](CONTRIBUTING.md) - Contribution guidelines

Quick Start (5 Minutes)

Get up and running in just a few commands. No complex setup needed.

# 1. Clone the repository

git clone https://github.com/nirholas/lyra-intel.git cd lyra-intel

2. Install (requires Python 3.9+)

pip install -e .

3. Quick scan - see what Lyra Intel finds in 30 seconds

python cli.py scan /path/to/any/code

4. Full analysis - comprehensive report

python cli.py analyze /path/to/code --output ./results.json

5. View results

cat results.json | jq . # Pretty print the JSON

6. (Optional) Start the web dashboard

python scripts/launch_dashboard.py

Then visit http://localhost:8080

What to Expect

After running scan, you'll see:

✅ Analyzing repository...

📊 Files analyzed: 156 📈 Total functions: 1,247 ⚠️ Issues found: 43 🔐 Security findings: 5

Running analyze produces detailed JSON with:

• Metrics: