analytics-datadeveloper-tools

GIS Data Conversion

ronantakizawa

by ronantakizawa

GIS Data Conversion enables seamless conversion between WKT, GeoJSON, CSV, TopoJSON, and KML with topology and reverse g

Provides a bridge between geographic data formats, enabling seamless conversion between WKT, GeoJSON, CSV, TopoJSON, and KML with support for reverse geocoding and topology preservation.

github stars

15

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Supports 5+ geographic data formatsPreserves topology during conversionIncludes reverse geocoding capability

best for

  • / GIS developers working with multiple data formats
  • / Data analysts processing geographic datasets
  • / Mapping applications requiring format conversion

capabilities

  • / Convert between WKT and GeoJSON formats
  • / Transform CSV data with coordinates to GeoJSON
  • / Convert TopoJSON to GeoJSON while preserving topology
  • / Transform KML files to GeoJSON format
  • / Perform reverse geocoding on coordinates
  • / Convert GeoJSON back to CSV format

what it does

Converts geographic data between multiple formats including WKT, GeoJSON, CSV, TopoJSON, and KML. Also provides reverse geocoding to convert coordinates into location information.

about

GIS Data Conversion is a community-built MCP server published by ronantakizawa that provides AI assistants with tools and capabilities via the Model Context Protocol. GIS Data Conversion enables seamless conversion between WKT, GeoJSON, CSV, TopoJSON, and KML with topology and reverse g It is categorized under analytics data, developer tools. This server exposes 6 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install GIS Data Conversion in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

GIS Data Conversion is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

GIS Data Conversion MCP

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<a href="https://glama.ai/mcp/servers/@ronantakizawa/gis-dataconvertersion-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@ronantakizawa/gis-dataconvertersion-mcp/badge" /> </a>

Copy of Untitled Design

The GIS Data Conversion MCP is an MCP (Model Context Protocol) server that gives LLMs access to geographic data conversion tools.

This server uses various GIS libraries to allow LLMs to convert between different geographic data formats, coordinate systems, and spatial references.

Features

  • Reverse Geocoding - Convert coordinates to location information
  • WKT/GeoJSON Conversion - Convert between Well-Known Text and GeoJSON formats
  • CSV/GeoJSON Conversion - Transform tabular data with coordinates to GeoJSON and vice versa
  • TopoJSON/GeoJSON Conversion - Convert between GeoJSON and TopoJSON (topology-preserving format)
  • KML/GeoJSON Conversion - Transform KML files to GeoJSON format

Demo

Reverse Geocoding

https://github.com/user-attachments/assets/e21b10c3-bb67-4322-9742-efa8c7d8b332

TopoJSON to GeoJSON

https://github.com/user-attachments/assets/a5d56051-8aed-48bb-8de1-820df8d34fe3

Installation

To use this server with Claude Desktop, you need to configure it in the MCP settings:

For macOS: Edit the file at '~/Library/Application Support/Claude/claude_desktop_config.json'

{
  "mcpServers": {
    "gis-dataconversion-mcp": {
    "command": "npx",
    "args": [
      "-y",
      "a11y-mcp-server"
    ]
   }
  }
}

For Windows: Edit the file at %APPDATA%\Claude\settings\claude_mcp_settings.json

For Linux: Edit the file at ~/.config/Claude/settings/claude_mcp_settings.json Replace /path/to/axe-mcp-server/build/index.js with the actual path to your compiled server file.

Available Tools

wkt_to_geojson

Converts Well-Known Text (WKT) to GeoJSON format.

geojson_to_wkt

Converts GeoJSON to Well-Known Text (WKT) format.

csv_to_geojson

Converts CSV with geographic data to GeoJSON.

Parameters:

  • csv (required): CSV string to convert
  • latfield (required): Field name for latitude
  • lonfield (required): Field name for longitude
  • delimiter (optional): CSV delimiter (default is comma)

geojson_to_csv

Converts GeoJSON to CSV format.

geojson_to_topojson

Converts GeoJSON to TopoJSON format (more compact with shared boundaries).

Parameters:

  • geojson (required): GeoJSON object to convert
  • objectName (optional): Name of the TopoJSON object to create (default: "data")
  • quantization (optional): Quantization parameter for simplification (default: 1e4, 0 to disable)

topojson_to_geojson

Converts TopoJSON to GeoJSON format.

Parameters:

  • geojson (required): GeoJSON object to convert
  • objectName (optional): Name of the TopoJSON object to create (default: "data")

kml_to_geojson

Converts KML to GeoJSON format.

geojson_to_kml

Converts GeoJSON to KML format.

coordinates_to_location

Converts latitude/longitude coordinates to location name using reverse geocoding.

Dependencies

  • @modelcontextprotocol/sdk
  • wellknown
  • csv2geojson
  • topojson-client
  • topojson-server
  • @tmcw/togeojson
  • xmldom

FAQ

What is the GIS Data Conversion MCP server?
GIS Data Conversion is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for GIS Data Conversion?
This profile displays 29 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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MCP server reviews

Ratings

4.629 reviews
  • Neel Verma· Dec 28, 2024

    Strong directory entry: GIS Data Conversion surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Nia Dixit· Dec 24, 2024

    According to our notes, GIS Data Conversion benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Kofi Rao· Dec 24, 2024

    We wired GIS Data Conversion into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Neel Thomas· Nov 15, 2024

    I recommend GIS Data Conversion for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Camila Zhang· Nov 15, 2024

    GIS Data Conversion is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Yash Thakker· Nov 3, 2024

    Strong directory entry: GIS Data Conversion surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Oct 22, 2024

    Useful MCP listing: GIS Data Conversion is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Neel Li· Oct 6, 2024

    We evaluated GIS Data Conversion against two servers with overlapping tools; this profile had the clearer scope statement.

  • Luis Bhatia· Oct 6, 2024

    GIS Data Conversion has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Luis Harris· Sep 13, 2024

    According to our notes, GIS Data Conversion benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

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