"AT&T" matching MCP servers:

140+ T-SQL static code analysis rules for SQL Database Projects

MCP server that indexes your codebase's public API at startup and serves it via compact tool responses, saving tokens vs reading source files.

AI reads your codebase like a book - one page at a time. Pharaoh gives it the index and a map of how every chapter connects.

MCP server that migrates SAP Module Pool programs to RAP applications interactively, using AI and SAP ADT REST APIs with human approval at each step.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

Enables AI assistants to search and analyze codebases using Abstract Syntax Tree (AST) pattern matching with ast-grep. Supports structural code search, pattern testing, and AST visualization across multiple programming languages.

Enables building MCP servers in TypeScript where tool schemas, descriptions, and validation are automatically generated from class methods, their TypeScript types, and JSDoc comments at compile time.

locidx

This MCP server enables AI models to analyze local Python codebases using abstract syntax trees, providing tools for file structure analysis, symbol search, import graphing, docstring auditing, and refactoring prompts without loading entire source files into context.

Provides deep structural analysis of TypeScript and JavaScript code via the TypeScript Compiler API, offering 20 tools for functions, types, call graphs, code quality, dead code detection, and IDE integration.

Exposes technical debt management to AI coding assistants, enabling them to find, prioritize, and resolve TODO/FIXME/BUG comments across codebases via MCP tools.

Enforces disciplined programming practices by requiring AI assistants to audit their work and produce verified outputs at each phase of development, following structured workflows for refactoring, feature development, and testing.

Enables AI coding agents to intelligently index and search codebases with sub-20ms retrieval, 8x memory compression, and cross-encoder reranking via MCP stdio.

Scans codebases for AI frameworks, checks EU AI Act compliance, and generates compliance reports, roadmaps, and audit-ready packages.

Static analysis engine that detects schema mismatches between data producers (like MCP servers) and consumers (like client code), preventing runtime errors by validating contracts at development time.

Exposes TypeScript Language Server Protocol functionality to AI agents, enabling them to query types at specific positions, find definitions and references, get diagnostics, run type tests, and type-check inline code just like in an IDE.

Provides comprehensive codebase analysis and semantic understanding through integrated knowledge graphs, enabling AI assistants to understand project structure, patterns, dependencies, and context through multiple analysis tools and format generators.

Enables local language models to request real-time peer review feedback from Google Gemini to improve response quality, accuracy, and completeness through AI collaboration.

Get the narrative and API documentation for the exact version of any of your dependencies. (Only Rust is supported at the moment.)

A Model Context Protocol server that facilitates communication between ABAP systems and MCP clients, providing tools for managing ABAP objects, handling transport requests, and performing code analysis to enhance ABAP development workflows.