"Linux Foundation" matching MCP servers:

Enables users to perform deterministic time series forecasting through Claude by running reproducible Python statistical and foundation models, providing tools for loading data, cross-validation, forecasting, anomaly detection, and exporting re-runnable manifests without any LLM involvement.

Integrates with IBM watsonx.ai to enable Claude Code to delegate text generation, chat, embeddings, and model listing to IBM foundation models like Granite and Llama.

MCP server for predictalot, providing streamable HTTP tools for zero-shot time-series forecasting with multiple foundation models and per-type ensembles. Tabular ML endpoints are currently HTTP-only.

Exposes geospatial foundation model inference as MCP tools for LLM agents, enabling building extraction, water segmentation, object detection, change detection, zero-shot scene classification, and embeddings on CPU.

MCP server that enables local Apple on-device Foundation Model access via any MCP client, supporting text generation, structured output, and multi-turn chat on macOS.

Enables AI agents to segment 2D and 3D biomedical images using Microsoft's MedImageParse foundation models via free-text prompts, returning masks and statistics. Supports both local stdio MCP server and a hosted Azure API Management gateway for remote agents like Microsoft Foundry.