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

Thirteen read-only Google Maps Platform tools for an agent: where a place is, what is around it, how long it takes to get there, and what the conditions are when it arrives.

Enables AI assistants to access Google Maps services including places search, details, directions, geocoding, and nearby search through natural language.

Enables AI assistants to search places, retrieve place details, reviews, photos, business posts, and contributor review histories from Google Maps through natural language, with no API keys or paid billing required.

MCP server exposing Google Maps Platform to MCP clients with seven tools for geocoding, place search/details, traffic-aware travel times, and time zones. Runs as a local stdio server or a containerized HTTP service with bearer auth, needing only a single API key.

A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.

Enables fetching comprehensive Google Maps place data, including full metadata and all gallery photos/videos at maximum resolution.

A Python MCP server for Metabase that enables AI assistants to query databases, manage dashboards, and interact with your Metabase instance.

Execute Python code via subprocess with timeout and error handling, returning stdout, stderr, and exit code.

Enables LLMs to interact with Python environments, execute code, manage files, and handle packages through the Model Context Protocol.

Provides AI agents with structured search results, place details, ratings, and contact info from Google Maps without requiring any API keys.

This MCP server provides direct access to ruff linting, formatting checks, and ty type-checking for Python projects, with token-efficient, structured output.

Python MCP server for SolidWorks automation with 109 tools covering the full CAD lifecycle. Enables AI-assisted design workflows through COM automation on Windows.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.

Enables AI coding assistants to browse Unreal Python API documentation, search classes and functions, and execute Python code in Unreal Editor.

Python Docs MCP Server gives AI coding agents local access to the official Python standard library docs. It can look up docs by Python version, return specific sections, and keep answers compact for clients like Claude Desktop, Cursor, and Codex. It runs without API keys or a hosted service.

Provides a production-ready FastMCP Python server boilerplate with structured logging, rate limiting, and config validation for building MCP servers compatible with Claude and other agents.

A Python MCP server that generates complete Vue 3 CRUD structures with Composition API, including components, services, stores, and routes.

MCP server providing automated code linting, rule explanations, and configuration templates for wemake-python-styleguide, with structured violation reports and offline rule database.

An MCP server that exposes Python debugging tools backed by debugpy, providing a focused debugging surface for local scripts.