{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_699a5ya92mxb","handle":"gdal-mcp","url":"https://wellknown.network/agents/gdal-mcp","links":{"self":"https://wellknown.network/agents/gdal-mcp/record.json","html":"https://wellknown.network/agents/gdal-mcp","markdown":"https://wellknown.network/agents/gdal-mcp/record.md","api":"https://wellknown.network/api/v1/agents/gdal-mcp","status":"https://wellknown.network/api/v1/agents/gdal-mcp/status","claim":"https://wellknown.network/agents/gdal-mcp/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/gdal-mcp/claim.json","badge":"https://wellknown.network/agents/gdal-mcp/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/gdal-mcp/history","tools":"https://wellknown.network/api/v1/agents/gdal-mcp/tools"},"ard":{"identifier":"urn:air::server:gdal-mcp","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"iflow-mcp_Wayfinder-Foundry-gdal-mcp","summary":"FastMCP server for Python-native GDAL ops (Rasterio/PyProj/pyogrio|Fiona/Shapely)","description":"# GDAL MCP\n\n**Geospatial AI with epistemic reasoning**\n\nGDAL MCP is a Model Context Protocol (MCP) server that provides AI agents with geospatial analysis capabilities while requiring them to **justify their methodological choices** through a reflection middleware system.\n\n**🎉 v1.1.1 Released (2025-10-26)** — Vector tool parity + cross-domain reflection validated  \n**🧠 Reflection System** — Domain-based epistemic reasoning that transcends data types  \n**⚡ 75% Cache Hit Rate** — Methodology reasoning carries across raster ↔ vector operations\n\n[![CI](https://github.com/Wayfinder-Foundry/gdal-mcp/actions/workflows/ci.yml/badge.svg)](https://github.com/Wayfinder-Foundry/gdal-mcp/actions/workflows/ci.yml)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)\n[![Python 3.11+](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org/downloads/)\n[![FastMCP 2.0](https://img.shields.io/badge/FastMCP-2.0-blue.svg)](https://github.com/jlowin/fastmcp)\n[![PyPI Downloads](https://static.pepy.tech/personalized-badge/gdal-mcp?period=total&units=INTERNATIONAL_SYSTEM&left_color=BLACK&right_color=GREEN&left_text=downloads)](https://pepy.tech/projects/gdal-mcp)\n\n---\n\n## 📚 Documentation\n\n- **[Quick Start](QUICKSTART.md)** - Installation, setup, and MCP configuration\n- **[Tools Reference](TOOLS.md)** - Complete tool documentation with examples\n- **[Environment Variables](docs/ENVIRONMENT_VARIABLES.md)** - Runtime configuration and tool surface controls\n- **[Vision](docs/VISION.md)** - Long-term roadmap and philosophy\n- **[Changelog](CHANGELOG.md)** - Release history and updates\n\n---\n\n## 🧠 The Reflection System\n\n### What Makes GDAL MCP Different?\n\nMost AI tool systems execute operations immediately when requested. 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