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Track, edit, query, and summarize expenses in a local SQLite database.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Expense Tracker MCP" yet — see the docs or source repo.
Add a new expense: date 2025-02-10, amount 48 CNY, category Dining, note Team lunch.
A success result confirming the new expense with its key fields.
Show all transportation expenses from the last month, listing date, amount, and notes.
A filtered list of matching expenses for review.
Summarize expenses for January 2025 by predefined category and include the total spending.
A category-level spending summary plus the overall monthly total.
Office workers can store daily expenses such as meals and transportation in a local database, then read, update, or delete incorrect entries later. This makes reimbursement tracking easier to maintain.
For analytics or personal budgeting, users can summarize expenses by predefined categories to quickly understand totals across spending types. It is useful for monthly expense reviews.
Developers can expose local SQLite-based expense tracking as an MCP service for AI assistants to call, including add, read, update, delete, and summarize operations. This fits lightweight local finance workflows.
It is an MCP server for expense tracking. Based on the description, it stores expenses in a local SQLite database and supports add, read, update, delete, and summarization operations.
Expense data is stored in a local SQLite database. The provided information does not specify the exact file path or schema.
According to the description, it supports adding, reading, updating, deleting, and summarizing expenses. It also uses predefined expense categories.
Track, list, and summarize expenses by category with local SQLite storage.
Track, manage, and summarize personal expenses with MongoDB-backed MCP tools.
Track, filter, and summarize personal expenses with SQLite-backed storage.
Track, categorize, and analyze expenses with fast summaries and lookups.
Manage and summarize expense records in a local SQLite database with natural language.
Track, list, and summarize categorized expenses through natural language.