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VinnyCarter05

Investment Statement MCP Server

by VinnyCarter05
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Python
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Investment Statement MCP Server

Parse and query investment statements from multiple institutions using natural language.

Features

  • Multi-Institution Support: Questrade, Interactive Brokers, Scotia iTRADE, TD Direct Investing

  • Hybrid Storage: SQLite for structured queries + LanceDB for semantic search

  • Natural Language Queries: Ask questions like "What were my dividends in Q3?" or "Show my SPY holdings"

  • Structured Tools: Programmatic access via MCP tools

  • Portfolio Analytics: Risk metrics, performance tracking, benchmark comparisons

  • Monte Carlo Simulation: 5-year portfolio projections with percentile analysis and visualizations

  • Archive Management: Keeps original PDFs/CSVs and parsed JSON for reference

Installation

# Install dependencies pip install -e ".[dev]"

Configuration

The server is configured via .mcp.json. Key environment variables:

  • LANCEDB_PATH: Vector database location (default: ./data/lancedb)

  • SQLITE_PATH: SQLite database location (default: ./data/statements.db)

  • PDF_ARCHIVE_PATH: Original PDF storage (default: ./data/pdfs)

  • JSON_ARCHIVE_PATH: Parsed JSON storage (default: ./data/json)

  • MODEL_NAME: Embedding model (default: all-MiniLM-L6-v2)

Usage

Starting the Server

python -m src.server

Indexing Statements

# Via MCP tool index_statement("/path/to/statement.pdf")

Querying Data

Natural Language Search:

search_statements("What were my total dividends in 2025?", limit=10)

Structured Queries:

get_holdings_by_symbol("SPY") get_transactions_by_date("2025-01-01", "2025-09-30") get_account_balance("51516162", "2025-09-30")

Monte Carlo Simulation:

# Run portfolio projection simulation result = run_monte_carlo_simulation( n_simulations=10000, # 10,000 simulation paths projection_years=5, # Project 5 years into the future account_numbers=None, # None = all accounts percentiles=[10, 25, 50, 75, 90] ) # Results saved to: # - Timestamped: data/reports/monte_carlo/2025-11-26_153034/ # - Latest: data/reports/monte_carlo/latest/ # # Output includes: # - 3 PNG charts (fan chart, distribution, confidence intervals) # - 3 CSV files (projections, summary, historical_returns)

See MONTE_CARLO.md for detailed documentation.

Resources

  • statements://catalog - List all indexed statements

  • statements://{statement_id} - Get specific statement

  • statements://{statement_id}/summary - Account summary

  • statements://{statement_id}/holdings - Holdings/positions

  • statements://{statement_id}/transactions - Transaction history

Supported Statements

Questrade

  • ✅ Account Summary (balances, FX rates, TFSA info)

  • ✅ Holdings/Positions (securities with cost basis, P&L)

  • ✅ Transactions (trades, dividends, deposits, withdrawals)

Interactive Brokers (Coming Soon)

  • ⏳ Planned

Scotia (Coming Soon)

  • ⏳ Planned

Development

# Run tests pytest # Run tests with coverage pytest --cov=src --cov-report=html # Format code black src tests # Lint code ruff check src tests

Architecture

  • FastMCP 2.0: MCP server framework

  • pymupdf4llm: PDF parsing optimized for LLMs

  • LanceDB: Vector database for semantic search

  • SQLite: Structured metadata storage

  • sentence-transformers: Embedding generation

License

MIT

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