About
Virtual Traveling Bot creates an immersive environment where you can control an avatar to virtually explore real-world locations on Google Maps. You can instruct the avatar where to travel and receive real-time progress updates with synthesized travel photos. Key features of Virtual Traveling Bot: - Avatar-based virtual navigation through Google Maps Street View with customizable routes - AI-powered image generation using Gemini nano-banana to composite the avatar into location photos - Real-time location tracking, address lookup, and nearby facilities discovery - Multiple travel modes including skip-to-destination and practice mode for testing - Support for both local development and remote deployment via Streamable-HTTP with Turso SQLite database backend - Social media integration for sharing travel narratives and immersive experiences
Tools 8
get_traveler_view_infoGet the address of the current traveler's location and information on nearby facilities,view snapshot
get_traveler_locationGet the address of the current traveler's location
tipsInform you of recommended actions for your device
get_settingGet current setting
get_traveler_infoget a traveler's setting.For example, traveler's name, the language traveler speak, Personality and speaking habits, etc.
set_traveler_infoset a traveler's setting.For example, traveler's name, the language traveler speak, Personality and speaking habits, etc.
start_traveler_journeyStart the traveler's journey to destination
stop_traveler_journeyStop the traveler's journey
README
Virtual Traveling bot environment for MCP
[](https://mseep.ai/app/073d88cc-277d-40b6-8c20-bcabf6c275e9) [](https://smithery.ai/server/@mfukushim/map-traveler-mcp)
English / Japanese
This is an MCP server that creates an environment for an avatar to virtually travel on Google Maps.
From an MCP client such as Claude Desktop, you can give instructions to the avatar and report on the progress of its journey with photos.
> Preparing for MCP Registry Support https://blog.modelcontextprotocol.io/posts/2025-09-08-mcp-registry-preview/
> Added gemini-2.5-flash-image-preview (nano-banana) to travel image generation
Support for nano-banana has been added. Nano-banana's semantic mask allows you to generate composite travel images in a short time without setting remBg. Although conventional image synthesis is still possible, we recommend using Gemini nano-banana.
> Supports both Streamable-HTTP and stdio (compliant with Smithery.ai's config interface)
It can be used as a stdio-type MCP as before, or as Streamable-HTTP.
Although it supports multiple users, the database API must be specified per session using the Smithery.ai config interface.
Since it supports both Streamable-HTTP and stdio, it is expected to work as is with the previous MCP client, but if you use the previous stdio version, please use v0.0.x (v0.0.81).
`` npx -y @mfukushim/map-traveler-mcp@0.0.81 ``
> Now supports librechat https://www.librechat.ai/.
> Now supports Smithery https://smithery.ai/server/@mfukushim/map-traveler-mcp (images are excluded because they are heavy to run).
> Now verified MseeP https://mseep.ai/app/mfukushim-map-traveler-mcp
Functions
#### MCP server tools function
The following functions can be used as an MCP server. The available functions vary depending on the settings and execution state.
You can specify the function name directly, but Claude LLM will automatically recognize it, so you can specify the operation in general terms.
Example: "Where are you now?" "Let's leave for Tokyo Station."
Related MCP Servers
AI Research Assistant
hamid-vakilzadeh
AI Research Assistant provides comprehensive access to millions of academic papers through the Semantic Scholar and arXiv databases. This MCP server enables AI coding assistants to perform intelligent literature searches, citation network analysis, and paper content extraction without requiring an API key. Key features include: - Advanced paper search with multi-filter support by year ranges, citation thresholds, field of study, and publication type - Title matching with confidence scoring for finding specific papers - Batch operations supporting up to 500 papers per request - Citation analysis and network exploration for understanding research relationships - Full-text PDF extraction from arXiv and Wiley open-access content (Wiley TDM token required for institutional access) - Rate limits of 100 requests per 5 minutes with options to request higher limits through Semantic Scholar
Linkup
LinkupPlatform
Linkup is a real-time web search and content extraction service that enables AI assistants to search the web and retrieve information from trusted sources. It provides source-backed answers with citations, making it ideal for fact-checking, news gathering, and research tasks. Key features of Linkup: - Real-time web search using natural language queries to find current information, news, and data - Page fetching to extract and read content from any webpage URL - Search depth modes: Standard for direct-answer queries and Deep for complex research across multiple sources - Source-backed results with citations and context from relevant, trustworthy websites - JavaScript rendering support for accessing dynamic content on JavaScript-heavy pages
Math-MCP
EthanHenrickson
Math-MCP is a computation server that enables Large Language Models (LLMs) to perform accurate numerical calculations through the Model Context Protocol. It provides precise mathematical operations via a simple API to overcome LLM limitations in arithmetic and statistical reasoning. Key features of Math-MCP: - Basic arithmetic operations: addition, subtraction, multiplication, division, modulo, and bulk summation - Statistical analysis functions: mean, median, mode, minimum, and maximum calculations - Rounding utilities: floor, ceiling, and nearest integer rounding - Trigonometric functions: sine, cosine, tangent, and their inverses with degrees and radians conversion support