"YAML" matching MCP servers:

A lightweight, powerful, and flexible workflow engine that executes tasks defined in YAML configuration files.

Provides safe, deterministic inspection, transformation, validation, and diffing of structured data (JSON, CSV, YAML, Parquet) via schema-aware MCP tools.

Open-source agentic schema layer. Define metrics once in YAML, query governed data from any warehouse (Snowflake, BigQuery, Databricks, PostgreSQL, DuckDB) via MCP.

Enables Claude to query a Postgres analytics schema via a read-only MCP server, with tools auto-generated from live database introspection and configurable SQL queries defined in YAML.

MCP server for the OrionBelt Semantic Layer. Enables LLMs to explore governed semantic models, compile YAML metric definitions into optimized SQL across 8 engines (BigQuery, ClickHouse, Databricks, Dremio, DuckDB, MySQL, PostgreSQL, Snowflake), and execute analytics queries via natural language. Works with Claude, Cursor, Windsurf, and Copilot.

An MCP server that provides tools for JSON validation, diffing, and transformation operations such as flattening and renaming. It also enables data format conversion between JSON, CSV, and YAML to streamline data processing for AI agents.

An MCP server that converts structured data (JSON, CSV, YAML, XML, etc.) to TOON format only when it saves tokens, with tools for conversion and analysis.

MCP server for Hydra ETL: lets AI assistants write declarative YAML ETL pipelines (CSV, Parquet, PostgreSQL, MySQL, MongoDB, APIs) and validate them before any data is read or written.