mcpnp
Verified Safeby parrisma
Overview
Augment LLM math capabilities by exposing common numpy and scipy operations as a Micro-Capability Platform (MCP) server.
Installation
docker build -f docker/Dockerfile.prod -t mcpnp_prd:latest . && docker run -p 9124:9124 mcpnp_prd:latestSecurity Notes
The server uses FastMCP for tool exposure and Pydantic for robust input validation, significantly mitigating injection risks. It leverages standard and well-audited libraries (numpy, scipy). No 'eval' or 'exec' is used dynamically. Error handling is present to catch exceptions during numerical operations. The test client uses a placeholder bearer token, indicating potential for API authentication. The server binds to 0.0.0.0 by default, which is common for containerized services but exposes it on all interfaces, though this is configurable.
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