MCP Server Marketplace: 950+ AI Tools
MCPize hosts 950+ Model Context Protocol servers for AI assistants, automation, databases, and search. One-click install for Claude, Cursor, VS Code, and any MCP client. One subscription gives you a single API key across every paid server.
Martech Audit
Martech Audit MCP server scans public websites to detect analytics tags, ad pixels, consent signals, and implementation risks such as misfiring trackers or missing consents. It reveals the martech stack in use and flags configuration issues. Digital marketers, web developers, and compliance analysts use it for site audits, pre-launch checks, and competitor analysis.
DB Health Analyzer
Executes health checks on database instances to evaluate performance metrics, resource consumption, and error patterns. Database administrators and DevOps teams use it for programmatic diagnostics integrated into monitoring pipelines and incident response.
KYC Policy Risk
KYC Policy Risk MCP server (kyc-policy-risk-mcp) supports evaluation of risks in Know Your Customer policies. Compliance officers and fintech developers integrate it to analyze policy vulnerabilities programmatically. Applications include automated checks during customer onboarding and regulatory audits.
Webhook Payload Linter
Validates webhook JSON payloads using AJV schema validation, lints request context for errors, and verifies HMAC signatures for Stripe and Shopify. This stateless server processes requests at zero API cost. Developers handling payment webhooks use it to ensure data integrity before application logic.
nextjs-prompt-polish-mcp
Optimizes prompts for React/Next.js in AI coding workflows through beautification, compression, guardrails, token estimation, and linting. Developers refine AI inputs to generate cleaner, more secure code snippets and components. Used in prompt engineering for Next.js app development to reduce token usage and enforce best practices.
marketing-attribution-modeler-mcp
Exposes MCP endpoints for building and applying marketing attribution models to assign credit to touchpoints like ads, emails, and social media in customer journeys. Data analysts and marketing teams use it to quantify channel ROI from conversion data. Applies models such as last-click, linear, or Markov chains via API calls.
Site Health Audit
Crawls websites to detect broken links, apply SEO and mobile-friendliness heuristics, compare results across audit runs, and optionally retrieve PageSpeed metrics. SEO specialists, web developers, and site maintainers use it to identify issues, monitor changes over time, and ensure site reliability before launches or updates.
Store Teardown
Audits Shopify storefronts for UX issues, product detail pages (PDPs), trust signals, and SEO factors, then outputs a prioritized backlog of conversion rate optimization (CRO) fixes. E-commerce store owners, growth marketers, and CRO analysts use it to pinpoint barriers to sales and plan targeted improvements.
Campaign ROI Planner
Campaign ROI Planner MCP server computes return on investment for marketing campaigns using inputs like budgets, channels, and projected metrics. It generates forecasts, simulates scenarios, and recommends allocations via API calls. Campaign managers and marketing analysts use it to evaluate strategies programmatically.
AI Backend BaaS
AI Backend BaaS MCP server delivers Backend-as-a-Service infrastructure optimized for AI/ML workloads, including serverless compute for model inference and managed data storage. Developers and ML engineers use it to deploy scalable backends for AI applications without handling servers or scaling logic.
Cross Channel Ads Ops
MCP server for cross-channel advertising operations. Enables programmatic handling of ad campaigns, placements, budgets, and performance data across platforms like social, search, and display. Ad operations engineers and marketing developers use it to integrate ad management into AI-driven workflows.
ai-usage-cost-analyzer-mcp
Fetches usage metrics from AI providers and computes costs based on token consumption, API calls, and billing rates. Outputs reports on expenses and trends across models and time periods. AI developers, ML engineers, and FinOps teams use it to track spending in LLM deployments.