"Analyzing Competitor SEO Strategies Through Google SERPs" matching MCP servers:

Enables AI assistants to create and modify Google Apps Script projects, manage versions and deployments, run functions, and inspect execution history through natural language.

Provides integration with the Google Apps Script API, allowing management of script projects, deployments, versions, and executions through any MCP-compatible client like Claude Desktop or VS Code.

This read-only MCP Server allows you to connect to Google BigQuery data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

An advanced MCP server that provides an agentic interface to Google's Gemini 3.1 models via Vertex AI, combining real-time Google Search, URL analysis, and Python code execution to solve complex multi-step research and data tasks.

Enables users to create, manage, and execute Google Apps Script projects through natural language. It provides comprehensive tools for code editing, function execution, deployment management, and monitoring script processes.

Lets any MCP-compatible agent use Google Colab or Jupyter runtimes as an execution backend, enabling code execution, notebook management, package installation, hardware introspection, training jobs, and file handling.

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to: Submit and validate constraint models Set model parameters Solve constraint satisfaction and optimization problems Retrieve and analyze solution

An MCP (Multi-Agent Conversation Protocol) Server that enables interaction with Google Workflows API, allowing management of workflow executions and definitions through natural language commands.

Enables MCP-compatible AI assistants to run Python code on Google Colab GPU/TPU runtimes, supporting accelerators like T4, A100, H100, with background execution and Google Drive integration.

An MCP server that enables AI applications to access 20+ model providers (including OpenAI, Anthropic, Google) through a unified interface for text and image generation.

Backtest PineScript v6 strategies locally from your AI agent: transpiles Pine to C++ and runs it on the deterministic, TradingView-validated PineForge engine via Docker. Tools for single backtests, parameter-grid sweeps, and Binance OHLCV fetch — no API key, data never leaves your machine.

A Model Context Protocol server that enables interaction with PostgreSQL databases for analyzing setups, debugging issues, managing schemas, migrating data, and monitoring performance.

A server providing tools for querying and analyzing Teradata databases, including database management, data quality assessment, and SQL execution capabilities through an MCP interface.

Enables local coding agents to manage disposable Colab GPU runtimes, restore and save Google Drive checkpoints, execute scripts, and safely stop VMs through MCP stdio tools.

Local-first MCP server for building and running reproducible Backtrader strategies offline, with tools to inspect datasets, manage drafts, and execute backtests via controlled subprocess runs. It supports multiple hosts including Claude, Codex, OpenCode, and OpenClaw through stdio.

MCP server for agentic interaction with the Lean theorem prover via LSP, providing tools for understanding, analyzing, and interacting with Lean projects.

A comprehensive learning project demonstrating MCP server implementation with tools for calculator operations, file management, and system information retrieval, including Google ADK integration patterns and best practices.

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.

A Model Context Protocol server that enables LLMs to analyze options chains, calculate Greeks, and evaluate basic options strategies through Yahoo Finance data.

Enables AI assistants to manage development workflows by running build commands, executing tests, analyzing package.json files, installing dependencies, and performing code linting. Supports multiple package managers (npm, yarn, pnpm) and provides detailed error reporting for development operations.