"CodeQL for Code Auditing" matching MCP servers:

Wraps the CodeQL Language Server Protocol to enable LLM agents to write CodeQL queries with intelligent code completion, hover information, and other language features.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Provides CodeQL language intelligence to AI agents via MCP, enabling completions, hover, definitions, references, diagnostics, formatting, and in-memory file updates for QL code.

Provides 28 MCP tools across 16 analysis engines for comprehensive Python code quality assessment, including complexity scoring, security scanning, dead code detection, dependency auditing, and test quality analysis.

Enables Codex CLI to perform code reviews on uncommitted changes via an MCP tool, keeping review context separate from the main session.

Enables automated security code auditing using LLM and MCP, including AST parsing, taint analysis, dataflow tracing, and automated PoC generation for multi-language codebases.

Enables AI assistants to interact with VS Code for language intelligence, debugging, and code execution.

Enables Claude Code to leverage OpenAI models for expert code review, deep architecture analysis, and security audits, with automatic markdown report generation.

Open-source AI code review MCP server for local git diff auditing with deterministic security rules and AI-powered analysis using any OpenAI-compatible model.

Enables AI-assisted development of CodeQL queries for security analysis through the Model Context Protocol. Provides tools for compiling, testing, and executing CodeQL queries across multiple programming languages.

A smart code retrieval tool based on Model Context Protocol that provides efficient and accurate code repository search capabilities for large language models.

Validates AI-generated Python: syntax, lint, security scan and deterministic repair.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

A unified developer toolkit for AI-assisted workflows. Task timing, doc drift detection, env validation, secret scanning, port conflict resolution, AI context generation, and license auditing — one MCP server, one install.

Helps AI assistants optimize Linux workloads on Arm64 by parsing perf report output, recommending NEON SIMD intrinsics for hot loops, and auditing Python dependency manifests for arm64 wheel availability — all offline and structured.

PCI DSS v4.0.1 compliance scanner for Go payment services, delivered as an MCP server. Every finding maps to a specific PCI DSS requirement ID. Taint-aware cardholder data flow analysis with PCI SSC FAQ semantics, designed to complement broad SAST tools like Semgrep and CodeQL - not replace them.

Provides a code search service via MCP, allowing AI clients to perform fast, indexed searches across large codebases using Zoekt, with support for filters like repository, language, and path.

Lets MCP-compatible AI assistants have read-only conversations with OpenAI Codex CLI for code analysis, review, and Q&A.

A code review tool that generates detailed HTML review documents by comparing branches or commits, with author filtering and intelligent analysis.

A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.