8 months ago
research-and-dataBeancount MCP Server is an experimental implementation that utilizes the Model Context Protocol (MCP) to enable AI assistants to query and analyze Beancount ledger files using Beancount Query Language (BQL) and the beanquery tool.
Overview
What is Beanquery MCP?
Beanquery MCP is an experimental server that implements the Model Context Protocol (MCP) to allow AI assistants to query and analyze Beancount ledger files using the Beancount Query Language (BQL).
How to use Beanquery MCP?
To use Beanquery MCP, set up the server by installing it in your environment, configure it with your Beancount ledger file, and run queries using the provided tools.
Key features of Beanquery MCP?
- Integration with Beancount ledger files for financial data analysis.
- Utilization of Beancount Query Language (BQL) for querying.
- Tools for setting ledger files and running queries.
Use cases of Beanquery MCP?
- Analyzing personal finance data stored in Beancount format.
- Querying financial records for insights and reporting.
- Enhancing AI assistants' capabilities in handling financial queries.
FAQ from Beanquery MCP?
- Is Beanquery MCP stable for production use?
No, it is an experimental implementation and should be used in a development environment.
- What are the prerequisites for running Beanquery MCP?
You need Python 3.10 or later and the uv tool for managing Python projects.
- How can I ensure my financial data is secure?
Be cautious with sensitive data, use self-hosted LLMs when possible, and review data being sent via MCP.