"How to interact with Google Maps using Python" matching MCP servers:

Enables validation, saving, publishing, and inspection of Galaxy Maps courses from local JSON files via Firebase integration.

Enables LLMs to interact with Google Ads accounts via tools like list_accounts and search_stream, using a standardized Model Context Protocol integration.

Enables LLMs to query live data from over 250+ sources via CData Python Connectors using natural language. Wraps connectors as a Model Context Protocol server.

A Machine Comprehension Protocol server that enables AI assistants to interact with Kestra workflows through natural language, supporting operations like flow management, executions, backfills, and other Kestra features.

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

Enables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.

Exposes the SiftingIO market-data SDK to AI assistants, enabling live prices, fundamental data, and market information retrieval.

Official Google Analytics MCP Server

MCP server that provides tools and resources for interacting with Google Ads API, enabling search, metadata retrieval, and account management through natural language.

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

Enables Large Language Models to interact with Google Ads API for querying campaigns, ad groups, and performing mutations like creating budgets and ads.

An MCP server for securely executing Python code, supporting STDIO, Streamable HTTP, and SSE transports, with easy deployment on Heroku.

Enterprise-grade MCP server integrating Claude AI capabilities, enabling AI-powered conversations, file operations, and system tools via the Model Context Protocol.

A Model Context Protocol (MCP) server for Chrome Enterprise Premium that exposes DLP rules, content detectors, connector policies, browser telemetry, and license management as MCP tools, enabling any MCP-compatible AI agent to inspect and configure a Chrome Enterprise environment.

Provides seamless access to TomTom's location services including search, routing, traffic and static maps data, enabling easy integration of precise geolocation data into AI workflows and development environments.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

百度地图

Model Context Protocol server to run Python code in a sandbox.