"Optimizing Meta ads campaigns and TikTok marketing" matching MCP servers:

MCP server for searching and analyzing 1C enterprise metadata and BSL code using a SQLite backend. Enables querying configuration structure, code routines, and performing compliance checks via natural language.

An advanced, AI-powered Model Context Protocol (MCP) server that acts as a comprehensive Growth Auditor, SEO Optimizer, and Code Fixer.

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Extracts minimal, relevant code context from multiple programming languages while analyzing diffs and optimizing imports to reduce token usage for AI assistants. Supports TypeScript/JavaScript, Python, Go, and Rust with token-aware caching.

Enables analyzing and optimizing context window token usage by measuring, compressing, and eliminating waste from MCP tool definitions.

MCP server providing Salesforce Marketing Cloud language intelligence — AMPscript, SSJS, and GTL — as Model Context Protocol tools, resources, and prompts for AI-assisted development and code review.

Enables IDE integration with a multi-agent AI pipeline for solving, reviewing, and optimizing code through adversarial peer review and security filtering.

Provides free and unlimited vision capabilities for AI coding assistants using the Groq API and Meta Llama 4 Vision model. It enables users to perform image analysis, OCR, UI layout description, and error diagnosis directly from screenshots and documents.

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).