"Apache Spark" matching MCP servers:

Read-only MCP server for accessing Spark/Ordernet brokerage accounts, including Meitav Trade, Psagot, IBI, Nesua, and Gaon. Enables querying holdings, transactions, orders, returns, security lookup, price history, standing orders, and market news via natural language.

Bridges Spark ASX trading platform with Claude Desktop via MCP, enabling natural language queries for live quotes, positions, P&L, and market analytics.

Enables auditing of extracted balance sheets, income statements, and cash flow reports by reconstructing complex document tables and verifying mathematical consistency and formula balancing. It also performs cross-reference resolution and sensitive PII redaction, returning structured matrices and validation telemetry over MCP to clients like Claude Desktop, Cursor, and Windsurf.

Enables autonomous financial agents to pool corporate treasury cash, rebalance liquidity, and optimize yield sweeps while enforcing double-entry ledger integrity, HMAC-SHA256 signature verification, and fraud-detection safety buffers that prevent overdrafts. Runs on pure Python standard library and plugs into MCP clients such as Claude Desktop, Cursor, and Windsurf.

Enables users to ingest carrier webhook events, detect transit anomalies such as stalled or failed deliveries, calculate compensation eligibility, and generate structured merchant claim payloads.

Enables quantitative risk analysis by calculating portfolio Value-at-Risk and Conditional VaR/Expected Shortfall across parametric and historical loss distributions, along with related option Greeks, Monte Carlo simulations, and fixed-income analytics through MCP.

Enables multi-party conditional escrow locking, autonomous proof-of-delivery release triggers, referral fee splits, and dispute freeze protection for agentic commerce and enterprise settlement workflows.

Enables autonomous financial agents and payment systems to analyze transaction streams in real time, detect velocity-based fraud patterns such as card testing, volume spikes, and account takeovers, and produce balanced ledger records with audit telemetry.

Enables autonomous financial agents to optimize payment recovery by analyzing decline-code retry windows and mitigating involuntary churn, while enforcing balanced double-entry ledger records, HMAC-SHA256 signature verification, and sliding-window fraud detection through an MCP-compatible interface.

Enables AI-driven banking workflows through secure interaction with Apache Fineract/MifosX Self-Service APIs, including authentication, account management, loans, savings, and transfers.

Enables fixed-income and quantitative risk analysis through MCP, computing bond cash flow present values, Macaulay and modified duration, and price convexity, alongside option Greeks, Monte Carlo simulations, VaR/CVaR, and Nelson-Siegel yield curve interpolation using only the Python standard library.

Enables analytical pricing of European options and calculation of first- and second-order Greeks including Delta, Gamma, Vega, Theta, and Rho through MCP. It also supports related quantitative finance analytics such as Monte Carlo simulations, VaR/CVaR, bond duration, and yield curve interpolation.

Enables MCP clients and autonomous financial agents to submit payment webhook events, journal entries, or transaction streams and receive cryptographically verified, balanced double-entry ledger records with HMAC signatures and hash-chained audit telemetry. It enforces debit/credit invariants and supports fraud detection for real-time accounting workflows.

Enables modeling and synthesis of creator paid amplification ROI, spark ads performance, and whitelisted return on ad spend (ROAS) for influencer marketing campaigns. It provides deterministic, zero-dependency calculations through MCP for use by AI agents and automation workflows.

Enables agents to monitor transaction streams, detect recurring charges and price creeping, flag zombie subscriptions, and generate automated cancellation workflows.

Enables users to model and interpolate zero-coupon yield curves using Nelson-Siegel parameters, fitting level, slope, curvature, and decay components from spot-rate data. It supports quantitative finance workflows through a standard MCP interface.

Enables synthesis of multi-tab financial models with circular-reference detection, formula dependency DAG compilation (SUMIFS, XLOOKUP, CAGR, NPV), and deterministic preview cell matrix evaluation through MCP.

Enables parsing of structured financial receipts, invoices, and bank statements, tolerance-based three-way reconciliation, detection of tax calculation drift and duplicate claims, and synthesis of double-entry bookkeeping journal entries.

Enables quantitative finance and risk analysis through MCP, including geometric Brownian motion Monte Carlo simulations, Black-Scholes Greeks, VaR/CVaR, bond duration/convexity, and Nelson-Siegel yield curve interpolation.

Enables users to register post-purchase receipts, monitor retailer price drops within price-match guarantee windows, verify eligibility, and synthesize automated refund claims.