Daloopa
AIOfficial MCPA financial-modeling copilot and fundamental-data provider that populates Excel and LLM workflows with structured public-company financials and KPIs.
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Paid
See pricing details
Daloopa
AIOfficial MCP
A financial-modeling copilot and fundamental-data provider that populates Excel and LLM workflows with structured public-company financials and KPIs.
-(0 Reviews)
Paid
See pricing details
About Daloopa
Daloopa delivers structured fundamental financial data and an AI copilot that automates financial-model population, updates, and time-series KPI extraction for investment research and modeling workflows. It ingests SEC filings, investor presentations, and other documents to extract statements and operational metrics, provides programmatic access via APIs and embeddable widgets, and integrates with LLM environments (via MCP/connectors) and Excel to keep models current and auditable. Its value lies in reducing manual data entry, ensuring source-linked traceability, and enabling faster, repeatable financial analysis across thousands of public companies.
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Key Features
Structured Fundamentals Extraction: Automatically extracts and normalizes financial statements and operational KPIs (income statement, balance sheet, cash flow, and custom metrics) from SEC filings, investor presentations, and PDFs into structured time-series formats.
Excel Model Integration: Populates and updates users' native Excel models with source-linked fundamental data and formulas, enabling one-click refreshes of models after earnings or data updates while preserving model structure.
LLM & MCP Connectors: Provides connectors and an HTTP API (used as an MCP/resource in platforms like Claude) so LLMs can query high-quality fundamentals and KPIs with source citations and integrate data into natural-language workflows.
Large Coverage Universe: Maintains coverage of thousands of public companies (noted as 3,500+ in partner docs), including historical quarter and fiscal-year time series and specialized operational metrics for sector-specific analysis.
Document-to-Spreadsheet Automation: Converts data from unstructured documents (CIMs, pitchbooks, investor decks) into clean Excel tables and time series to accelerate due diligence and model-building.
Embeddable Widget & Developer Tools: Offers embeddable demo widgets and developer examples (GitHub repos) to streamline integration into internal apps, portals, or research tools for interactive data access.
Auditability & Source Linking: Every data point links back to the original filing or document, enabling verification, transparent audit trails, and defensible research outputs.
Programmatic access to fundamentals, financial statements, and operational KPIs (cited to SEC filings and investor materials)
Coverage of thousands of public companies (documented as 3,500+ in integrated product docs)
Model Context Protocol (MCP) / HTTP connector support for integration with LLMs (example: Claude MCP HTTP transport)
Embeddable widget with demo code (GitHub repo) for web embedding
Excel integration to push/update data directly into user spreadsheets and models
Document extraction: parse PDFs, CIMs, investor decks into structured Excel-compatible outputs
Time series data and quarter-level KPI histories for multi-period analysis
Server-side authentication token handling recommended for embed/API usage
Provides audit trails and citation metadata for sourced data
Non-real-time (post-earnings) data updates; not positioned as intraday real-time feed
Use Cases
Automated Model Refreshes: Updating multi-sheet Excel financial models automatically after quarterly earnings releases, preserving formulas and assumptions while refreshing underlying fundamentals.
LLM-Powered Financial Queries: Connecting Daloopa to LLMs (via MCP or API) so analysts can ask natural-language questions about KPIs, run time-series comparisons, and receive answers with source citations.
Due Diligence & Document Extraction: Extracting financial schedules and metrics from acquisition CIMs, investor decks, or PDFs into structured spreadsheets to accelerate M&A or credit diligence.
Peer Benchmarking and Screening: Pulling standardized metrics across a set of 3–10 peer companies to compute relative performance, growth rates, and operational efficiency comparisons for investment memos.
Portfolio Monitoring & Reporting: Feeding up-to-date fundamentals into portfolio dashboards to monitor positions, calculate valuation metrics (DCF inputs, multiples), and generate audit-ready reports.
Model Building & Validation: Generating clean starter models (DCF, LBO, comparables) from extracted data and validating assumptions by comparing extracted time series against user models.
Automate updating and ramping of Excel financial models with authoritative fundamentals
Enable LLMs to query structured financial data and KPIs with source citations
Extract structured financial tables from SEC filings and offering documents into Excel
Benchmark and time-series analysis across peer companies for investment research
Due diligence workflows that require consolidated, cited company financials
Generate spreadsheet formulas and rebuild model structure from raw filings
MCP Server
https://daloopa.com/products/mcp💡 MCP (Model Context Protocol) enables AI assistants to securely interact with local and remote resources.
