GeoSpatial MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| mcp_geo_convertA | 在不同坐标系统之间转换坐标。支持BD09（百度）、GCJ02（火星）、WGS84（GPS）和Web Mercator投影坐标系统之间的互相转换。 |
| mcp_geo_calculate_distanceA | 计算折线的距离。支持多种坐标系统输入，内部会先转换为WGS84坐标，再通过Web Mercator投影进行平面距离计算。适用于中小尺度的距离计算。 |
| mcp_geo_calculate_areaA | 计算多边形面积。支持多种坐标系统输入，内部会先转换为WGS84坐标，再通过Web Mercator投影进行平面面积计算。多边形无需手动闭合。适用于中小尺度的面积计算。 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: calculate_area for polygon area, calculate_distance for polyline distance, and convert for coordinate system conversion. There is no overlap in functionality, making tool selection straightforward for an agent.
All tool names follow a consistent pattern: mcp_geo_ followed by a verb (calculate or convert) and a noun (area, distance, or no noun for convert). This predictability enhances usability and reduces confusion.
With only 3 tools, the server feels thin for a geospatial domain, which typically involves more operations like buffering, intersection, or spatial queries. While the tools cover basic calculations and conversion, the scope is limited, potentially requiring agents to work around missing functionality.
The tool set is severely incomplete for geospatial operations. It lacks essential CRUD or lifecycle coverage, such as creating or querying spatial data, performing spatial joins, or handling more complex analyses like buffering or overlay operations. This will likely cause agent failures in broader geospatial tasks.