"A tool for generating and live previewing Mermaid diagrams from code" matching MCP servers:

Enables agents to search official Mermaid diagram syntax documentation and validate Mermaid diagram code before presenting it to users, ensuring syntactically correct flowcharts, sequence diagrams, class diagrams, and other Mermaid visualizations.

Enables AI coding agents to list, read, create, update, delete, and render PlantUML and Mermaid diagrams, and check them against the actual codebase to detect architecture drift.

A tool for validating Mermaid diagram syntax through CLI and MCP interfaces, providing real-time error checking and line-specific feedback. It enables AI assistants to self-validate and debug generated diagrams across all Mermaid types, ensuring valid visual documentation.

Enables AI assistants to analyze code repositories and generate self-contained interactive HTML5/SVG architecture diagrams from project structure or existing Mermaid diagrams, fully air-gapped with no external dependencies.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Enables agents to analyze codebases (local or GitHub) and automatically generate Mermaid diagrams rendered as PNG images via Kroki, providing visual understanding of project structure and flow through file discovery, reading, and diagram generation.

Validates Mermaid diagrams with comprehensive grammar parsing supporting 28+ diagram types. Processes markdown files, ZIP archives, and direct input with detailed error reporting and enterprise-grade performance capabilities.

CodeGuard MCP is a real-time AI code security scanning tool used to detect vulnerabilities, keys, and compliance issues in AI-generated code, and is suitable for code security reviews in development environments

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.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

A local, SQLite-backed code index for Claude Code, exposed over MCP, enabling targeted code retrieval without external APIs.

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

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.

embedded code search engine CLI -AST based that just works - improves speed and efficiency for coding agent

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

An MCP server that provides local code quality analysis for AI coding assistants, supporting file analysis, git diff review, and full project scanning with quality scoring.

Gemini-powered MCP server for automated code review, analysis, and documentation.

Fast pre-commit dependency gate for AI-assisted code changes. Answers "is this safe to commit?" with a PASS/WARN/BLOCK verdict in seconds, so you can catch risky blast radius before a bad commit, not after it. No database, no heavy setup.

An MCP server for intelligently reading Java source code, supporting extraction from Maven dependencies and local projects with dual decompilers.

MCP server for comprehensive code analysis, navigation, and quality assessment across 25+ programming languages.

Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.

Enables agents to run semantic search across one or more local project directories by automatically maintaining a LAN-local Qdrant index with Ollama embeddings. Indexing, staleness checks, and incremental updates happen transparently, so users can query code by meaning without managing collections, chunks, or hashes.

Checks a code repository without running it: Safe, Works and Complete scores with an A-F grade, catching leaked keys, dangerous calls, invented or lookalike packages, broken imports and missing project files. Standard-library Python; MCP tools scan, orphans and explain.

AI-powered continuous code assistant for Cursor, VS Code, Antigravity, and Claude Code via MCP, providing tools for code review, testing, documentation, and quality analysis.

Connects Kimi Code with Claude Code, enabling Claude to delegate bulk codebase reading to Kimi (256K context) for cost savings, while Claude focuses on reasoning and code edits.

Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.

An installable MCP server that reviews diffs/PRs against a target repository's own coding conventions, learned via RAG over its code, docs, and lint config, citing specific file:line sources.

Enables AI assistants to perform comprehensive code reviews of local uncommitted changes by combining git diffs with static analysis from linters like ESLint and TypeScript. Returns structured JSON feedback with findings, suggestions, and quality assessments powered by Google's Gemini CLI.

Strict AI code reviewer powered by Groq. Finds bugs, vulnerabilities and security issues in your code. Supports analyze, compare versions, explain code, generate tests, and HTML reports.

A Model Context Protocol (MCP) server that helps large language models index, search, and analyze code repositories with minimal setup