Verifiable spatial reasoning for LLMs: geodesic distance, topology and CRS computed by a geometry engine, with source...
Copy the install, test the workflow, then decide if it earns a permanent slot.
Fresh repo activity plus visible builder pull. This is the kind of tool people test before it turns obvious.
Copy the install, test the workflow, then decide if it earns a permanent slot.
You can test this quickly and remove it cleanly if it misses.
GitHub health unknown. no security policy. Fresh enough repo health and manageable issue load keep the risk controlled.
AI Agent
Universal
Model
Multiple
Fastest way to find out if geospark belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
claude mcp add geospark -- npx geosparkRun this first. You will know quickly if the workflow earns a permanent slot.
claude mcp remove geosparkNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude.json └─ mcp_servers/ └─ geospark ← registers here
Verifiable spatial reasoning for LLMs: geodesic distance, topology and CRS computed by a geometry engine, with sources and licences on every answer. MCP server, REST API, Python library.
Source: GitHub repository
Source check: October 22, 2026
Upstream commit: October 22, 2026
Repository state: Not marked archived
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