pybme-mcp

Enables LLM agents to perform Bayesian Maximum Entropy geostatistical analysis through natural language rather than code, supporting spatial, network, and physics-informed uncertainty modeling.

→ wiesnerfriedman/pybme-mcp · listed on glama

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// key findings

✅

No credential exfiltration, no sensitive file access, no obfuscation

Static analysis found nothing flowing your secrets to unexpected places.

✅

Open source with a license and README

Anyone can audit the code, the license is declared, and the publisher documents what it does.

// full audit trail

The full breakdown of what we checked, the deductions that landed, the network hosts, the dependency advisories, and concrete fix guidance is available to verified publishers.

// improvement guidance — verified publishers only

We have 4 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.

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[![M8ven Score](https://m8ven.ai/badge/mcp/wiesnerfriedman-pybme-mcp-19vrt7)](https://m8ven.ai/mcp/wiesnerfriedman-pybme-mcp-19vrt7)

commit: d0ec5dab5b22a6ad87de322c0187fa923b819b6b

code hash: b39c7169d307e98200f6542d6f2f2ea97da7a32cc37a8e132480f29c5e87b381

verified: 6/17/2026, 12:00:58 PM

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