"Zaim" matching MCP servers:

A Model Context Protocol (MCP) server that integrates the FAIM time series forecasting SDK with any MCP-compatible AI assistant, enabling AI-powered forecasting capabilities.

A unified backend MCP server that aggregates and filters data from external services like Zaim, GitHub, Google, and Notion, providing cross-cutting views via MCP and REST API without heavy AI inference.

Enables LLM agents to interact with a SQLMesh project, providing model metadata, column-level lineage, plan previews, audits/tests, and environment diffs, with optional apply/run actions.

Exposes local data profiling, PII classification, and plan-based cleansing against DuckDB, Postgres, or SQLMesh tables through four tools (list_tables, profile, propose_cleansing_plan, apply_cleansing_plan). All reasoning stays aggregate-only — format signatures, counts, and match rates rather than raw cell values — and cleaning plans execute only after validation against a fixed operation vocabulary and explicit confirmation.