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

Enables AI agents to inspect, create, and edit 1C metadata and managed forms in a configurator XML dump without manual XML editing, using metadata_check for dry-run validation and metadata_apply for writes. It enforces platform dump rules, preserves formatting, and supports operations such as object creation, property changes, renaming, role generation, and form amendments.

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.

Enables AI agents to analyze and diff binaries by driving Ghidra headless or inside its GUI, exposing native reverse-engineering tools such as listing functions and segments, searching strings, decompiling, disassembling, and following cross-references. Ships with a devcontainer and supports local stdio or remote HTTP deployment.

Enables MCP clients to load eight on-demand coding skills and inspect project repositories through bounded, read-only map, search, read, diff, checks, and style tools. It keeps context lean by loading skill bodies only when needed and limiting repository scan and output sizes.

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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 models to reach all 170 reverse-engineering tools through four meta-tools for searching, schema lookup, calling, and bundle switching, so only a tiny fraction of the tool context is loaded by default. Function bundles can be activated or deactivated at runtime without restarting the host.

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 pixi-aware quality gates for linting, type checking, security scanning, complexity analysis, baselines, trend analysis, automated fixes, and comprehensive reporting through a small three-meta-tool MCP interface.

Enables read-only TwinCAT ADS diagnostics and symbol reads, offline PLC XML source-edit previews with diffs, and template-based Scope acquisition candidate generation over MCP stdio.

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.

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

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.

Autonomous AppSec & DAST code and website security scanner across 12 security domains (260+ controls) with 3-Layer Triage.

Next-gen AST codebase map, token compression (70%~85% savings), and context packaging engine for AI coding agents & IDEs.

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.

Verificate combines 17 applications each designed to address a separate issue with AI Coding supported with a Frontier AI Model. This allows you to Vibe Code with confidence and even dropped down to a more basic model with a better outcome.

MCP server that provides AI assistants with structured access to codebases via LogicStamp Context, enabling component analysis, dependency graphs, drift detection, and token-optimized context delivery.

Enables AI agents to run deterministic database intelligence tasks including natural-language-to-SQL synthesis, AST SQL auditing and optimization, schema migration diffing, SQL transpilation, index and normalization advice, PII scrubbing, fixture generation, connection-pool sizing, isolation-hazard auditing, and ORM model compilation over Streamable HTTP or stdio.

Enables AI coding agents to efficiently navigate and understand large codebases by providing tools for entry point location, call chain analysis, and impact assessment, reducing context consumption and model costs.

An MCP server that gives autonomous coding agents deterministic, schema-validated tools for EVM smart contract development — security scanning, gas profiling, compiler diagnostics, and transaction simulation.

Enables LLMs to apply Martin Fowler's 71+ refactoring patterns to codebases through a pluggable, language-agnostic architecture. Supports previewing and applying refactorings, analyzing code smells, and inspecting code structure with safe-by-default operations.

An MCP server that scans local codebases for quantum-vulnerable cryptography (secp256k1, Ed25519, RSA, etc.) and CI signing commands, classifying each finding as quantum-broken, post-quantum, or neither. It runs entirely locally with no network calls, providing a deterministic inventory for AI agents.