"High-Quality PDF Extraction to Text with Tokenization and Accurate Processing of Complex Layouts" matching MCP servers:

Enables coding agents to turn OpenSpec intents and Git changes into revision-bound proofs by planning, selecting, and running the smallest safe protection set, then verifying composite verdicts and explaining evidence or unresolved states.

A zero-dependency local MCP server that audits and auto-fixes React/Next.js frontend code smells, unused imports, and responsive UI issues

Enables pixi-aware quality gates for linting, type checking, security scanning, complexity analysis, baselines, trend analysis, automated fixes, and comprehensive reporting through a small three-meta-tool MCP interface.

Converts vector PDF circuit schematics into evidence-preserving SchematicIR JSON with tools to inspect, convert, and validate schematic PDFs.

Hybrid code quality analysis server combining fast logic-based checks with AI-powered deep analysis, offering tools for summaries, quick wins, and trend tracking.

Enables Claude-powered pre-push code review, blocking bad commits by analyzing diffs with Anthropic's models.

Enables Cursor and Codex agents to audit Agent Skill structure (frontmatter, broken links, missing files), analyze dependencies for undeclared, unused or vulnerable packages via OSV, and run 28 local bug and code-quality rules with SonarQube-style A–E ratings. It can also optionally pull issues, metrics and quality-gate status from SonarQube or SonarCloud, or scan and upload results.

Enables code agents to run risk-based Jev quality reviews on focused diffs through a read-only MCP tool, returning structured scores and weakness hints without modifying code.

🚀 Kill the Junior AI Era. 🤖 Level up your AI code to Principal standards. No more sloppy lines or junior mistakes. Automated ESLint ✨ TypeScript 🔧 Prettier 🎨 SonarQube 🛡️ Security 🔒 Complexity 📊 in seconds. High-stakes quality, forced to ship only the best. ⚡🏆 Goodbye, bad code. Hello, Principal Engineer. 🚀✨

Provides deterministic Python code quality analysis using flake8, mypy, McCabe, and vulture, enabling LLMs to access real linting and type checking results.

Connects AI coding assistants to PyCharm's code quality inspections and optionally SonarQube for IDE, providing unified, de-duplicated code analysis results without uploading source code.

One MCP server for golangci-lint, govulncheck, and nilaway — a unified Diagnostic\[] array with consistent file:line:column navigation, parallel execution, and zero-config auto-install - for golang development.

Enables checking project files like Dockerfile, .nvmrc, and CI workflows to determine whether pinned runtime, database, and OS versions are still supported, providing end-of-life dates, latest patches, and upgrade targets for 470+ products.

Provides tools to test regex patterns for correctness, performance (ReDoS), and memory usage, and suggests safe rewrites. Enables LLMs to iterate on regex generation with verifiable feedback.

Enables AI assistants and developers to analyze code for language-specific best practices and idiomatic patterns across programming languages, CI automation, and configuration formats.

Helps with cicd work, failed tests in automation and also tmmi/iso scans en reports.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.