Data Dictionary MCP

The Data Dictionary MCP is a specialized Model Context Protocol server that empowers AI assistants to automatically convert raw database artifacts—whether they are JSON, CSV, or plain text dumps—into polished, Wikipedia‑style data dictionaries. By orchestrating a team of AI agents through MCP, the server tackles the tedious and error‑prone task of manually documenting database schemas. The result is a consistent, human‑readable reference that can be shared with developers, analysts, and stakeholders who need quick insight into table structures, field meanings, and inter‑table relationships.

The core value of this server lies in its ability to bridge the gap between machine‑readable database files and the narrative format that people naturally use when exploring data. Developers who typically spend hours writing README tables or scraping schema metadata now benefit from an automated pipeline that extracts column names, data types, and inferred constraints. The AI agents then enrich each field with descriptive text, highlighting business relevance or data lineage, and identify relationships such as foreign keys or one‑to‑many associations. The final output mimics the familiar layout of Wikipedia infoboxes, making it instantly recognizable and easy to integrate into documentation portals or internal wikis.

Key capabilities include:

• Multi‑format ingestion: Accepts JSON, CSV, and plain text dumps, with a roadmap to support additional formats.
• AI‑driven analysis: Uses language models to infer semantic meaning and relational structure without requiring explicit schema definitions.
• MCP orchestration: Coordinates separate agents for parsing, describing, and validating content, ensuring each step is modular and testable.
• Schema unification: Normalizes disparate input structures into a common representation that can be queried or exported.
• Human‑friendly output: Generates tables and prose in a Wikipedia‑style format, complete with headings, bullet lists, and cross‑references.

In practice, the server shines in data migration projects, API documentation, or any scenario where a clean, accessible schema is needed quickly. For example, when onboarding new data scientists to a legacy database, the MCP can produce an instant dictionary that eliminates the need for manual research. Similarly, data governance teams can use it to audit and publish schema changes as part of compliance reporting.

By integrating seamlessly with existing AI workflows—leveraging MCP’s tool and prompt extensions—the Data Dictionary MCP allows developers to embed schema generation into chat‑based assistants, automated CI pipelines, or web services. Its unique advantage is the combination of automated insight extraction and structured, publish‑ready formatting, reducing both time to value and the risk of human error in database documentation.