Skip to main content
Glama
199,156 tools. Last updated 2026-06-13 14:20

"Python code quality improvement and codebase diagram generation tools" matching MCP tools:

  • Analyze code already in context to receive structured findings, a quality score, and improvement suggestions. Supports security, performance, quality, or comprehensive reviews.
    Apache 2.0
  • Generate architecture diagrams from Python code using the diagrams package. Create AWS, Kubernetes, and custom diagrams by writing code that defines components and connections.
    Apache 2.0
  • Retrieve system environment details including OS, Python version, installed libraries, and execution mode before generating code. Helps tailor code to the current setup and avoid errors.
    MIT
  • Validate diagram specifications before generation to check node validity, connection references, and cluster memberships, returning validation results with any errors or warnings.
    MIT
  • Measure codebase vocabulary health: convention coverage, naming consistency, and semantic cluster cohesion. Identify top inconsistencies and uncovered identifiers to improve code quality.
    MIT

Matching MCP Servers

  • -
    license
    -
    quality
    -
    maintenance
    Provides deterministic Python code quality analysis using flake8, mypy, McCabe, and vulture, enabling LLMs to access real linting and type checking results.
    Last updated
    1

Matching MCP Connectors

  • Corporate travel: search and book flights, hotels, rail and transfers, manage orders.

  • Create and manage trackable QR codes with scan tracking, analytics, and dynamic URL updates.

  • Analyze code and data to troubleshoot issues, review quality, audit security, suggest refactoring, or assess test coverage with configurable depth and focus areas.
    MIT
  • Run custom Python code in Fusion 360 for operations not available through standard tools. Access the application, design, and root component directly.
    MIT
  • Review source code to identify bugs, security vulnerabilities, code quality issues, strengths, and recommended actions. Get an overall score from 1 to 10.
    MIT
  • Analyze source code using AST parsing to extract functions, classes, and imports, generate Mermaid diagrams (class, flowchart, dependency), and optionally apply AI for quality insights, security issues, and improvement suggestions.
    MIT
  • Execute Python code in a sandboxed environment based on natural language prompts. Generate and run code, then return both the code and execution results.
    MIT
  • Improves developer prompts by adding quality requirements, codebase context, and tool recommendations to help AI coding assistants generate better structured code.
    MIT
  • Analyze code architecture to assess design patterns, SOLID principles, scalability, and security. Submit your code, language, and specific question to receive tailored improvement recommendations.
    MIT
  • Analyze Nostr pubkey follow lists to assess quality, identify ghost followers, measure diversity, and provide improvement suggestions for better network connections.
    MIT
  • Analyze Python code with Ruff, ty, and Vulture to detect linting issues, type errors, and dead code for comprehensive code quality improvement.
    MIT