"Accessing Facebook Settings and Preferences" matching MCP servers:

locidx

Provides AI assistants with direct access to Laravel documentation, coding rules, and implementation templates stored locally. It enables searching documentation, retrieving design system guides, and accessing domain-specific code examples to streamline Laravel development.

An MCP server that runs Python project checks through pytest, Ruff, and basedpyright, with configurable settings and stdio/HTTP transport.

Enables AI assistants to work with Chapel code, including compiling, linting, and accessing educational primers.

Enables AI coding agents to interact with Gel databases by executing queries, testing changes in transactions, and accessing code examples and rules for advanced workflows.

Enables AI agents to compile, execute, and check Almide code for syntax or compilation errors. It provides tools for generating ASTs and accessing language grammar resources.

Enables persistent storage and semantic search of coding preferences, patterns, and implementations using Mem0, allowing AI agents to remember and retrieve development best practices across sessions.

Exposes Django runtime information (settings, apps, URLs, models, migrations) as MCP resources for AI agents to inspect a live Django project without static analysis.

Twelve tools combine per-function complexity and branch coverage to rank work and check edited functions against their ceiling. Packets include source, uncovered lines, change-coupled files and near-duplicates. MCP calls can write local caches and metadata; they do not run test suites, edit source or claim work.

Provides AI assistants with progressive code intelligence to explore repository structure, find symbols, and assess the impact of changes using ast-grep.

Verifies npm packages for security risks before installation, checking advisories, install scripts, typosquatting, and other factors, providing safe/block verdicts.

An MCP server giving coding agents context-window-aware code search and safe, atomic multi-file edits — built to cut token usage on large codebases without sacrificing correctness.

Enables querying any GitHub, GitLab, or Bitbucket repository and getting AI-generated answers about the codebase, powered by Gemini.

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

MCP server for AI-assisted development on the Lampa open-source TV app, providing read-only access to the source tree with 41 tools and 5 resources for structured analysis, planning, editing, and validation.

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.

Offline MCP server for SAP ABAP static analysis, ABAP Cloud readiness scoring, and RAP scaffolding. It enables AI agents to lint ABAP source, compare reworks, check released APIs, and generate RAP business objects without needing an SAP system.

Enables asking natural-language questions about any GitHub repository and receiving answers grounded in the actual code, with read-only enforcement and automatic repository fetching.

Connects AI assistants like Claude to PHP's XDebug debugger for runtime inspection, breakpoint control, and variable tracking, enabling natural language debugging of PHP applications.

Copy/paste (duplicate code) detection for codebases. The jscpd detector's built-in MCP server lets AI agents check snippets and files for duplication against a scanned project over stdio (jscpd --mcp).