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Repository Intelligence

Analyze codebases with AST parsing, semantic search, complexity metrics, security scanning, and repository discovery tools.

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Install Repository Intelligence

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "repository-intelligence": {
      "command": "npx",
      "args": [
        "-y",
        "lyra-intel-mcp"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Install not yet sandbox-tested— the server itself is confirmed live (we called its tools/list endpoint). The stdio install command is a separate, ongoing check.

Overview

Repository Intelligence connects MCP clients to Lyra Intel for large-scale codebase analysis, security scanning, and repository discovery. Its tools combine AST parsing, dependency mapping, complexity measurement, semantic code search, and forensic checks for dead code or documentation gaps. GitHub discovery tools can identify MCP crypto tool repositories, analyze their definitions and security, and submit results to the Lyra Registry. Reach for it when you need to understand a large repository, assess changes, investigate security issues, or generate technical documentation.

Use cases

  • Analyze an unfamiliar monorepo before making architectural changes
  • Search a large codebase for semantically related implementations
  • Review branch or commit changes for impact and risk
  • Find dead code, secrets, vulnerabilities, and documentation gaps
  • Generate API and architecture documentation from code analysis

Key features

  • AST-based codebase analysis
  • ML-powered semantic code search
  • Cyclomatic, cognitive, and Halstead complexity metrics
  • Security scanning for vulnerabilities and hardcoded secrets
  • Git diff impact and risk analysis
  • GitHub MCP tool discovery and registry submission

Tools12

What Repository Intelligence lets your agent do. Expand a tool for its parameters.

Verified live~931 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

7/7 checks healthy over the last 30d

What it can do

From the 12 tools this server returned when we ran it.

Handles credentials · 1Read-only tools · 12
Network at startup3 connections
Files written at startupNone
Install scriptsNone
npm provenanceNot published
Package age40 days
Maintainers1

Observed 2026-10-25 in an isolated sandbox. A description of reach, not a security audit.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 12d ago via OSV.dev · lyra-intel-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars29Stargazers on the source repository.
npm downloads28Package downloads in the last 30 days.
Last commit4d agoMost recent push to the default branch.
Tools exposed12Callable tools this server registers over MCP.
Directory activity1 viewsConfig copies, upvotes, and views on AllMCPs.

How Repository Intelligence works

What Repository Intelligence does

Repository Intelligence exposes Lyra Intel’s code intelligence functions through MCP. It is designed for projects ranging from small repositories to large monorepos and supports analysis tasks that go beyond simple keyword search or linting.

The core analysis path examines source structure with AST parsing, maps dependencies, calculates code complexity, and scans for security concerns. Semantic search uses ML-powered embeddings to locate relevant snippets by meaning rather than exact text matches. Forensic analysis adds checks for unused functions, classes, technical debt, orphaned documentation, and mismatches between code and documentation.

The server also includes a separate discovery workflow for GitHub. That workflow finds MCP crypto tool repositories, extracts and evaluates their tool definitions, checks security and quality, and can submit analyzed tools to the Lyra Registry.

How it works

analyze-codebase runs a broad repository assessment covering structure, dependencies, complexity, and security. More focused tools expose individual results: search-code performs semantic lookup, get-complexity returns cyclomatic, cognitive, and Halstead metrics, and get-security-issues reports vulnerabilities, hardcoded secrets, and compliance issues.

diff-analyze compares commits or branches and evaluates affected functions, classes, impact, and risk. generate-docs turns analysis results into API documentation, README content, or architecture documentation in multiple formats. forensic-scan looks for dead code, technical debt, unused symbols, and code-documentation discrepancies.

The discovery tools form a pipeline: scan GitHub, analyze selected repositories, optionally submit analyzed tools, and inspect discovery statistics such as recent runs, tools found, and submission rates.

Setup and configuration

The project supports Python 3.9 or newer and provides Docker and Kubernetes deployment options. Its architecture includes local analysis for development, distributed processing for larger workloads, and cloud-oriented scaling for very large repositories.

Storage options include SQLite for local projects, PostgreSQL for production deployments, and BigQuery for large-scale analysis results. A cache layer can use memory, files, or Redis. AI-assisted analysis can use OpenAI, Anthropic, or local models such as Ollama and llama.cpp.

The broader platform also includes REST API, authentication, OAuth 2.0, LDAP, and role-based access features. These capabilities are relevant when deploying Lyra Intel as a shared service rather than using it only for local analysis.

Tools and capabilities

  • analyze-codebase: Run combined codebase analysis.
  • search-code: Find code semantically with ML-powered embeddings.
  • get-complexity: Retrieve cyclomatic, cognitive, and Halstead metrics.
  • get-security-issues: Identify vulnerabilities, secrets, and compliance issues.
  • diff-analyze: Assess changes between commits or branches.
  • generate-docs: Produce API, README, and architecture documentation.
  • forensic-scan: Detect dead code, technical debt, and documentation gaps.
  • discovery-scan-github: Find MCP crypto tool repositories on GitHub.
  • discovery-analyze-repo: Extract tool definitions and assess repository quality and security.
  • discovery-submit-tool: Submit previously analyzed tools to the Lyra Registry.
  • discovery-run-pipeline: Run the discovery, analysis, and optional submission sequence.
  • discovery-get-stats: View discovery activity and result statistics.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about Repository Intelligence

Repository Intelligence is an MCP server that connects AI clients to Lyra Intel for codebase analysis, semantic code search, complexity measurement, security scanning, diff analysis, documentation generation, forensic checks, and GitHub MCP tool discovery. It is intended for projects ranging from small repositories to large monorepos.

Repository Intelligence supports Python 3.9 or newer and can be deployed with Docker or Kubernetes. The platform also describes local, distributed, and cloud-oriented analysis modes for different repository sizes.

Repository Intelligence scans codebases for vulnerabilities, hardcoded secrets, and compliance issues. Its security capabilities include OWASP-oriented checks, SQL injection detection, CVE and advisory tracking, and custom security patterns.

Yes. Repository Intelligence can scan GitHub for MCP crypto tool repositories, analyze repositories to extract tool definitions and assess quality and security, submit analyzed tools to the Lyra Registry, and report discovery statistics.

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