wiesnerfriedman/pybme-mcp

pybme-mcp is a thin integration layer between the Anthropic-led Model Context Protocol (MCP) and the pyBME geostatistics library. With only 1 star and 0 days of age, it currently exists as a utility wrapper rather than a mature product. Its defensibility is very low because the logic is essentially 'glue code'—exposing existing library functions as MCP tools. While Bayesian Maximum Entropy (BME) is a sophisticated niche in environmental science and epidemiology, the specific implementation of this server doesn't contain proprietary algorithms or data moats. Frontier labs (OpenAI/Anthropic) are unlikely to target this specific niche, but as LLMs become better at writing and executing their own Python code (e.g., via Code Interpreter), the need for a dedicated MCP server for specific scientific libraries may diminish. The primary value is as a convenience for researchers using MCP-compatible agents (like Claude Desktop) who want to perform geostatistical modeling without manual coding.