Structured Data Tools

About

This tool provides a robust MCP server designed to prevent AI coding assistants from corrupting structured data files. It addresses common issues like hallucinated fields, invalid syntax, and broken formatting by offering a strict, round-trip safe interface. AI agents can perform token-efficient queries, validate changes against schemas (including SchemaStore.org), and apply safe modifications while preserving comments and formatting across JSON, YAML, and TOML formats. It also supports LMQL-powered constraint validation for guided generation, ensuring data integrity and reliable operations.

Key Features

• Safe modifications that validate changes before writing and preserve comments/formatting
• Constraint validation using LMQL for guided generation and input checks
• Multi-format support for JSON, YAML, and TOML through a unified interface
• Schema validation to enforce correctness using SchemaStore.org or custom schemas
• 3 GitHub stars
• Token-efficient queries to extract specific data without loading entire files

Use Cases

• Enable AI assistants to safely convert configuration files between JSON, YAML, and TOML formats.
• Allow AI agents to read specific configuration values from complex structured files (e.g., GitLab CI, pyproject.toml).
• Validate structured data files against defined JSON schemas to ensure syntax and data integrity.