Extracts key-value pairs from arbitrary, noisy, or unstructured text using LLMs and provides type-safe output in JSON, YAML, or TOML formats.
This MCP server leverages LLMs (GPT-4.1-mini) and pydantic-ai to extract key-value pairs from unstructured text, even when it's noisy or complex. Its automatic key discovery identifies and extracts relevant data without predefined keys, making it ideal for diverse and unpredictable datasets. The server's multi-step pipeline, including multilingual preprocessing with spaCy NER, LLM-based type annotation and evaluation, and Pydantic validation, ensures type safety and consistent output in JSON, YAML, or TOML formats, enhancing extraction accuracy and reliability for downstream applications.