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官方说明10 个来源MCP 服务8 天前
mahdin75/gis-mcp

mahdin75/gis-mcp

🏠 - Geospatial operations and transformations using GIS libraries
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add gis-mcp -- npx -y gis-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
198 ★ · mahdin75/gis-mcp · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 10 个来源列出
评分构成
综合分 1,003 · 198 ★ · 10 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 mahdin75/gis-mcp;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

GIS MCP Server

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

GIS-MCP is an open-source Model Context Protocol (MCP) server that connects AI assistants and Large Language Models (LLMs) with GIS and geospatial operations.
It enables AI agents to perform geospatial analysis, spatial data processing, vector and raster operations, coordinate transformations, spatial statistics, mapping, and other GIS workflows through MCP-compatible clients.
🌐 **Official Documentation:** https://gis-mcp.com
📦 **PyPI:** https://pypi.org/project/gis-mcp/
💻 **Source Code:** https://github.com/mahdin75/gis-mcp
> **92+ GIS tools** across Shapely, GeoPandas, PyProj, Rasterio, PySAL, visualization, satellite imagery, climate, ecology, movement, and land-cover data.
| Category | Badges |
| ---------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **Package** | |
| **Installation & Transport** | |
| **Storage** | |
| **Data Sources** | |
| **Agentic AI** | |
| **Community** | |
✨ Want to perform accurate geospatial analysis in your chatbot? ✨
Install GIS-MCP and transform your AI's spatial capabilities!
> Current version is 0.15.0 (Beta):
>
> We welcome contributions and developers to join us in building this project.
🎥 Demo
📋 Table of Contents
- Features
- Storage
- Prerequisites
- Vibe Coding
- Installation
- Docker Installation
- pip Installation
- Development Installation
- Build Your First GIS AI Agent
- Available Functions
- Shapely Functions
- PyProj Functions
- GeoPandas Functions
- Rasterio Functions
- PySAL Functions
- Visualization Functions
- Static Map Functions
- Interactive Web Map Functions
- Administrative Boundaries Functions
- Climate Data Functions
- Ecology Data Functions
- Movement Data Functions
- Land Cover Data Functions
- Satellite Imagery Functions
- Client Development
- Planned Features
- Contributing
- License
- Related Projects
- Support
- Badges
🚀 Features
GIS MCP Server empowers AI assistants with advanced geospatial intelligence. Key features include:
- 🔹 **Comprehensive Geometry Operations** – Perform intersection, union, buffer, difference, and other geometric transformations with ease.
- 🔹 **Advanced Coordinate Transformations** – Effortlessly reproject and transform geometries between coordinate reference systems.
- 🔹 **Accurate Measurements** – Compute distances, areas, lengths, and centroids precisely.
- 🔹 **Spatial Analysis & Validation** – Validate geometries, run proximity checks, and perform spatial overlays or joins.
- 🔹 **Raster & Vector Support** – Process raster layers, compute indices like NDVI, clip, resample, and merge with vector data.
- 🔹 **Spatial Statistics & Modeling** – Leverage PySAL for spatial autocorrelation, clustering, and neighborhood analysis.
- 🔹 **Easy Integration** – Connect seamlessly with MCP-compatible clients like Claude Desktop or Cursor IDE.
- 🔹 **HTTP/SSE Transport** – Run as HTTP service with RESTful storage endpoints for file upload/download operations.
- 🔹 **Flexible Storage** – Local filesystem by default, or Google Cloud Storage when you want files in a GCS bucket.
- 🔹 **Flexible & Extensible** – Supports Python-based GIS libraries and is ready for custom tools or workflow extensions.
> 🌟 **Tip:** With GIS MCP Server, your AI can now “think spatially,” unlocking new capabilities for environmental analysis, mapping, and location intelligence.
---
💾 Storage
GIS MCP Server supports two storage backends for file upload, download, and tool outputs:
| Backend | When to use | Configure with |
| ------- | ----------- | -------------- |
| **Local filesystem** | Default; files on disk (including Docker volumes) | --storage-path or GIS_MCP_STORAGE_PATH |
来源
awesome · https://github.com/mahdin75/gis-mcp
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