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OpenStreetMap MCP Server

@NERVsystems

リポジトリ

基本情報

カテゴリ

メディアとデザイン

ライセンス

MIT

トランスポート

stdio

作者

NERVsystems

OpenStreetMap MCP Server について

OpenStreetMap MCP server providing precision geospatial tools for LLMs via Model Context Protocol. Features geocoding, routing, nearby places, neighborhood analysis, EV charging stations, and more.

#golang#geocoding#mcp#openstreetmap#geospatial#routing#ev-charging#neighborhood-analysis#anthropic-claude#llm-tools#model-context-protocol#mcp-server

OpenStreetMap MCP Server の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

OpenStreetMap MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is OpenStreetMap MCP Server?

OpenStreetMap MCP Server is a Go implementation of the Model Context Protocol (MCP) that enables LLMs to interact with geospatial data from OpenStreetMap. It provides a suite of tools for geocoding, routing, place discovery, and geographic analysis, designed for precision, performance, and ease of integration with MCP desktop clients.

How to use OpenStreetMap MCP Server?

The server is configured and invoked through MCP‑compatible desktop clients. It exposes a set of tool endpoints (e.g., geocode_address, route_fetch, find_nearby_places) that accept JSON parameters. No specific installation or configuration commands are detailed in the README beyond the standard MCP setup.

Key features of OpenStreetMap MCP Server

  • Geocoding and reverse geocoding of addresses and coordinates
  • Route fetching and turn‑by‑turn directions via OSRM
  • Finding nearby points of interest by category and radius
  • Bounding box, centroid, and distance calculations
  • Polyline encoding/decoding and route sampling
  • EV charging station and parking facility queries
  • Neighborhood livability and commute analysis
  • Map image retrieval in SVG format with metadata

Use cases of OpenStreetMap MCP Server

  • Build AI‑powered travel planners that suggest meeting points and routes
  • Automate real‑estate relocation analysis with livability scores
  • Enable conversational search for amenities like schools, cafés, or EV chargers
  • Analyze commute options between home and work locations
  • Generate visual map snapshots for location‑aware applications

よくある質問

1

What external services does the server depend on?

The server uses the OSRM routing service for route fetching and OpenStreetMap API data for queries. Polyline tools are self‑contained.

2

How are errors handled during geocoding?

Enhanced error responses include structured error codes, diagnostic messages, and specific suggestions for fixing failed queries.

3

Can I combine tools for custom workflows?

Yes. Tools are designed as composable primitives with uniform interfaces, allowing LLMs to chain them (e.g., `bbox_from_points → osm_query_bbox → filter_tags → sort_by_distance`) for unforeseen workflows.

4

What transport does the server use?

The server implements the Model Context Protocol (MCP) standard. No specific transport (stdio/HTTP) is mentioned in the README beyond the MCP framework.

5

What runtime environment is required?

The server is written in Go and runs as a standalone binary. No additional runtime dependencies are listed.

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