A Model Context Protocol (MCP) server implementation that connects Large Language Models (LLMs) to GIS operations using GIS libraries, enabling AI assistants to perform geospatial operations and transformations.
Security
Low Risk
Quality
Watch · 66
Install
ready
Audit version
audit-standard-v2
Source metrics come from upstream registries/repositories. Platform metrics come from user actions on SkillTrust and are protected by dedupe/rate-limit anti-abuse rules.
A Model Context Protocol (MCP) server implementation that connects Large Language Models (LLMs) to GIS operations using GIS libraries, enabling AI assistants to perform geospatial operations and transformations.
• Add explicit When to Use / Guidelines sections.
• Provide at least one concrete input-output example.
• Publish versioned changelog and update cadence.
• Document compatibility and breaking-change policy.
• Expand capability limits and boundary conditions.
Is this a security certification?
No. SkillTrust audit is advisory and should be combined with your own review controls.
Can I install directly from this page?
No one-click install is provided. Use command guidance and run in your controlled environment.
Latest repository push timestamp.
git clone https://github.com/mahdin75/gis-mcp.gitInstall method: script-backed
Quick install
Install paths
repository clonelocal runtime dependenciesshell accessPreflight checks
Post-install signal
Installed successfully? Send an activation signal to improve ranking quality over time.
Audit score 20 / 100. Risk guidance is advisory only; review evidence before install.
• Add troubleshooting and FAQ for common failures.
• Improve discoverability through verified source channels.
• Publish usage examples to increase activation quality.
• Reduce shell/file/network scope and document least privilege.
• Expose explicit provenance, dependency pinning, and security notes.
• Provide structured install + rollback steps for each supported agent.
• Mark official/verified status and keep metadata timestamps fresh.
Potentially stale; validate compatibility before install.
Audit guidance: 20 / 100 · low
Scores with similar values can still differ in confidence; use evidence and risk lines below for final install judgment.
Risk 20 · Δ +0 · Findings 3
Apr 3, 2026 · auto
Latest low risk result from audit-standard-v2.