"Maintaining Consistent Behavior in System Prompts" matching MCP servers:

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Provides structured instructions to Cursor for generating comprehensive system summaries of Node.js/TypeScript codebases.

Read-only MCP tools for coding agents to audit deployment targets, detect fabricated code, review backlog, database schema, analytics, ML models, architecture docs, and decision lenses.

Enables AI agents to create, validate, and export UML system models using structured MSON format. Supports generating PlantUML and Mermaid diagrams with direct export to System Designer macOS application.

Fetches, summarizes, and reviews GitHub code diffs with asynchronous processing for large diffs.

A Python-based system that provides AI-powered code reviews through simulated expert personas like Martin Fowler and Robert C. Martin, using the Model Context Protocol (MCP).

Transforms code repositories and development documentation into a queryable Neo4j knowledge graph, enabling AI assistants to perform intelligent code analysis, dependency mapping, impact assessment, and automated documentation generation across 15+ programming languages.

An MCP server that analyzes Python codebases using AST, stores code elements in a vector database, and enables natural language queries about code structure and functionality using RAG with Google's Gemini models.

Provides real-time TBC Bank development standards compliance checking and code review tools. Integrates with GitHub Copilot and development workflows to automatically enforce coding guidelines and reduce violations.

An enterprise-grade AI processing platform that provides advanced code analysis, automated documentation generation, security scanning, and knowledge extraction capabilities through a scalable MCP architecture. Features iterative neural processing, support for 100+ programming languages, and real-time streaming updates.

MCP server for ai-scanner that enables AI agents to scan codebases for LLM usage, AI frameworks, and exposed secrets.

Enables Claude Web to securely inspect, search, and modify local project files through a sandboxed MCP server with atomic writes, path traversal protection, and sensitive file blocking.

MCP server that exposes pre-extracted facts about code behavior, design decisions, and assumptions to AI agents, saving time and tokens by avoiding direct source file reading.

Enables auto-configuration and validation of React components against a glassmorphic design token system using an AST correction engine. It supports managing UI presets, enforcing design uniformity in Monaco IDE, and exporting tokens as CSS, Tailwind, or JavaScript variables.

Provides code-aware context compression by stripping comments, docstrings, and whitespace while maintaining full logic fidelity for AI agents. It features tools for architectural mapping, symbol searching, and token-budgeted multi-file reading.

AI access to SAP ECC and on-premise S/4HANA: natural-language table queries, ABAP source reads, where-used lookups, syntax checks, dumps and background jobs — served by an in-system ABAP add-on behind a single ICF node, with no BTP, ADT or RISE dependency. Every call runs under the calling user's own SAP authorizations and is audit-logged inside the customer's system; the connector is MIT-licensed

A Model Context Protocol server that accelerates CodeIgniter-inspired PHP framework development by generating, validating, and maintaining idiomatic MVC plus Services/Repository code via 7 tools and 4 resources.

A local-first MCP preflight system to help AI inspect Python repositories before generating code, enabling reuse, extend, or create decisions. Currently in early development with only foundational modules implemented.

Provides real-time security risk assessment for AI coding prompts, analyzing potential dangers, blast radius, and complexity before code execution in Cursor.

Provides tools to retrieve deterministic prompts for rewriting any Node.js project to production-quality TypeScript, supporting incremental and single-pass workflows.