Data Dictionary MCP
@jonahkeegan
About Data Dictionary MCP
A Model Context Protocol (MCP) server that coordinates AI agents to transform database tables into Wikipedia-style data dictionaries.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"data-dictionary-mcp": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}Tools
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Overview
What is Data Dictionary MCP?
Data Dictionary MCP is a Model Context Protocol server that automates the conversion of database tables into Wikipedia-style data dictionaries. It uses AI agents coordinated via MCP to analyze, describe, and verify database structures.
How to use Data Dictionary MCP?
Clone the repository, create a Python 3.9+ virtual environment, install dependencies from requirements.txt, then run python src/main.py.
Key features of Data Dictionary MCP
- Multi-Format Support: JSON, CSV, and Plain Text files
- AI-Powered Analysis: generate field descriptions and relationships
- MCP Integration: coordinate AI agents via the protocol
- Schema Extraction: unify schemas from various formats
- Wikipedia-Style Output: familiar, accessible presentation format
Use cases of Data Dictionary MCP
- Create comprehensive data dictionaries from database schemas
- Automatically describe fields and identify relationships with AI
- Convert JSON, CSV, and plain text into structured dictionaries
- Leverage AI agents to verify and improve dictionary accuracy
FAQ from Data Dictionary MCP
What file formats are supported?
JSON, CSV, and Plain Text are supported; more formats are planned.
What are the prerequisites?
Python 3.9+, Git, and pip or poetry for dependency management.
Is this project production-ready?
No, it is in active development. See the Project Roadmap for details.
How can I contribute?
Contributions are welcome via Pull Requests.
What license does this project use?
MIT License.
Frequently asked questions
What file formats are supported?
JSON, CSV, and Plain Text are supported; more formats are planned.
What are the prerequisites?
Python 3.9+, Git, and pip or poetry for dependency management.
Is this project production-ready?
No, it is in active development. See the Project Roadmap for details.
How can I contribute?
Contributions are welcome via Pull Requests.
What license does this project use?
MIT License.
Basic information
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