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.
XAU Risk Journal
Bridges TradingView alerts for XAU/USD trading to perform local risk checks and log entries to an SQLite database. It processes incoming alerts, evaluates risk parameters like position sizing, and persists trade journals locally. Quantitative traders and algo developers use it to automate compliant trade execution without external dependencies.
FinOps Export Analyzer
Ingests and analyzes cloud cost export files from providers like AWS CUR, Azure, and GCP billing data. Breaks down spend by service, tag, region, and time; detects anomalies and trends. FinOps engineers and cloud finance analysts use it to audit bills and identify savings.
social-orders-inbox-mcp
social-orders-inbox-mcp MCP server provides access to inboxes for orders received via social media channels like DMs on Instagram or Facebook Messenger. It enables programmatic retrieval and management of order messages. E-commerce developers and automation engineers use it to integrate social sales into backend systems.
Actions Workflow
Actions Workflow MCP server (actions-workflow-mcp) enables programmatic interaction with GitHub Actions workflows. It supports dispatching events to trigger runs, querying run statuses, and accessing execution logs via API calls. Developers and DevOps teams use it to integrate AI agents into CI/CD pipelines for automated testing and deployment.
import-unit-economics-mcp
Imports unit economics data such as customer acquisition cost (CAC), lifetime value (LTV), and gross margins into model contexts via the MCP protocol. Developers and financial analysts use it to integrate business metrics into AI-driven analysis pipelines. Applications include profitability modeling for SaaS products and startup financial forecasting.
LLM Cost Monitor
Tracks LLM API spending across providers including OpenAI, Anthropic, and Gemini. Delivers cost calculators, model comparisons, and budget projections directly in AI development workflows. AI engineers and developers use it to monitor expenses and optimize provider selection.
LLM Cost Estimator
Estimates costs for LLM API usage by converting token counts into dollar amounts using a curated pricing catalog from major providers. Operates without needing access to billing APIs. Developers and AI engineers use it to forecast expenses for inference runs, batch processing, and model fine-tuning in production planning.
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.