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kukapay/nearby-search-mcp

by Various

An MCP server for nearby place searches with IP-based location detection.

K

MCP

kukapay/nearby-search-mcp

Added 1 June 2026

Overview

An MCP server that lets AI agents search for nearby places using IP-based geolocation. It accepts natural language queries and returns structured results from a places API.

Best for

Best for
Developers building location-aware AI agents or chatbots that need quick, approximate place search without user permission prompts.

Use cases

  • Find restaurants or services near the user's current location
  • Integrate location-aware search into AI assistants or chatbots
  • Build automated tools that respond to location-based queries

How to use

Install

uv add "mcp[cli]" httpx python-dotenv

Tools exposed

  • mcp
  • uv

Example client config

{\n  "mcpServers": {\n    "nearby-search": {\n      "command": "uv",\n      "args": ["--directory", "path/to/nearby-search-mcp", "run", "main.py"],\n      "env": {\n        "GOOGLE_API_KEY": "your google api key"\n      }\n    }\n  }\n}

Notes

An MCP server that lets AI agents search for nearby places using IP-based geolocation. It accepts natural language queries and returns structured results from a places API.

22 stars on GitHub. Last updated 2025-03-27. Licensed MIT.

Use cases

  • Find restaurants or services near the user’s current location
  • Integrate location-aware search into AI assistants or chatbots
  • Build automated tools that respond to location-based queries

Pros

  • Simple setup with no API key required for basic use
  • Works with any MCP-compatible client or host
  • Lightweight Python implementation

Cons

  • IP-based location is less accurate than GPS or user-provided coordinates
  • Limited to 22 GitHub stars, indicating a small community and potential lack of support
  • Dependent on external places API availability and rate limits

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Simple setup with no API key required for basic use
  • Works with any MCP-compatible client or host
  • Lightweight Python implementation

Cons

  • IP-based location is less accurate than GPS or user-provided coordinates
  • Limited to 22 GitHub stars, indicating a small community and potential lack of support
  • Dependent on external places API availability and rate limits
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