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My Finance MCP Server

My Finance MCP Server

by xinrong-meng

My Finance MCP Server

Bare-bones Model Context Protocol server that lets Claude store personal finance transactions and later query them via semantic search. Transactions are persisted in ChromaDB for vector search plus a JSON ledger for backup.

Run it alongside Claude Desktop and you get an AI bookkeeper that remembers your receipts, statements, and portfolios—then answers natural language questions about spending trends, allocations, or anything else you upload.

Setup

Install

uv sync

Run

uv run my_finance_mcp.py

Configure Claude Desktop

Add to ~/.claude_desktop_config.json:

{
  "mcpServers": {
    "my-finance": {
      "command": "uv",
      "args": [
        "run",
        "--project",
        "/path/to/my_finance",
        "/path/to/my_finance/my_finance_mcp.py"
      ]
    }
  }
}

Related MCP server: Finance MCP Server

Usage

Exposed tools:

  • store_transactions(transactions) – ingest structured transactions (Claude will extract them from uploaded docs)

  • query_financial_history(query) – run semantic search across everything stored

  • list_transactions(limit=20, offset=0, category=None) – page through the JSON ledger to inspect what’s saved and see each transaction’s index

  • delete_transactions(indices=None, delete_all=False, confirm=False) – delete entries by index or wipe them all (requires confirm=True)

  1. Upload financial data to Claude

  2. Say: "Store this transaction data"

  3. Claude calls the MCP server to save it

  4. Later ask: "How much did I spend on groceries last month?"

  5. Claude searches your historical data via MCP

  6. Use "Show me the stored transactions" or "Delete transaction xx" to invoke the management tools

Example Claude Desktop interaction

User: Remember these portfolio positions for later analysis.
Claude: I'll help you store your portfolio positions from the uploaded CSV file for later analysis. Let me read the file and process the data..
Perfect! I've stored your portfolio positions from November 6, 2025 in your finance system. Here's a summary of what was recorded:...

User: List my stored transactions
Claude: Here are your current stored transactions (4 total):...

User: Delete VXUS - International Stock ETF transaction
Claude: The VXUS - International Stock ETF transaction has been successfully deleted from your stored transactions.

User: List all transactions
Claude: Here are your current stored transactions (3 total):...

Data Storage

  • ~/.my_finance_mcp/financial_data/ - ChromaDB vector database (created automatically)

  • ~/.my_finance_mcp/transactions.json - JSON backup of all transactions

Set the MY_FINANCE_MCP_DIR environment variable before launching Claude if you want to store data in a different directory.

Available Tools

4 tools
delete_transactionsA
Delete transactions from both the JSON ledger and ChromaDB.

Args:
    indices: List of transaction indices (from list_transactions) to delete
    delete_all: Set to true to delete all transactions
    confirm: Must be true to actually perform deletion (safety guard)

Returns:
    Status message describing the deletion result

Inputs: indices, delete_all, confirm. Returns: result

list_transactionsA
List stored transactions from the JSON ledger with optional pagination and filtering.

Args:
    limit: Maximum number of transactions to return (default 20)
    offset: Number of transactions to skip from the beginning (default 0)
    category: Optional category filter (case-insensitive)

Returns:
    Dictionary containing total count, pagination info, and transactions with index field

Inputs: limit, offset, category. Returns: result

query_financial_historyC
Search through all stored financial data using semantic search.

Args:
    query: Search query string to find relevant transactions

Returns:
    Formatted summary of matching transactions with totals

Inputs: query (required). Returns: result

store_transactionsA
Parse and store transaction data from uploaded financial documents.

If you receive unstructured financial data (statements, receipts, CSV files, etc.),
extract transactions into the format: [{"date": "YYYY-MM-DD", "amount": number, "description": "string", "category": "string"}]

Args:
    transactions: List of transaction dictionaries, each containing:
        - date: Transaction date (string, format: YYYY-MM-DD)
        - amount: Transaction amount (number, can be negative for expenses)
        - description: Transaction description (string)
        - category: Transaction category (string, optional, e.g. "Food", "Transport", "Bills")

Returns:
    Success message with count of stored transactions

Inputs: transactions (required). Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3.4/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a distinct and non-overlapping purpose: list_transactions retrieves data, store_transactions adds new data, delete_transactions removes data, and query_financial_history performs semantic search. The descriptions clearly differentiate their functions, with no ambiguity in selection.

    Naming Consistency4/5

    Three tools follow a consistent verb_noun pattern (list_transactions, store_transactions, delete_transactions), but query_financial_history deviates slightly with a different verb style. The naming is still readable and mostly predictable, with only minor inconsistency.

    Tool Count3/5

    With only 4 tools, the set feels thin for a finance management server, lacking operations like update_transactions, get_transaction_by_id, or category management. While the tools cover basic CRUD and search, the scope suggests more functionality is needed for comprehensive financial handling.

    Completeness2/5

    There are significant gaps in the tool surface for a finance domain. The server supports create (store_transactions), read (list_transactions, query_financial_history), and delete (delete_transactions), but lacks update operations (e.g., modify_transaction) and essential features like budget tracking, reporting, or category CRUD, which will limit agent effectiveness.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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