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Bigdata-com (Preview)

Unlock institutional-grade financial data with the Bigdata.com connector. Instantly retrieve real-time news, comprehensive company tearsheets, and corporate event calendars. Sourced from well-trusted providers, this tool empowers financial institutions to make data-driven decisions by delivering accurate, structured market intelligence directly into your workflow.

This connector is available in the following products and regions:

Service Class Regions
Copilot Studio Premium All Power Automate regions except the following:
     -   US Government (GCC)
     -   US Government (GCC High)
     -   China Cloud operated by 21Vianet
     -   US Department of Defense (DoD)
Logic Apps Standard All Logic Apps regions except the following:
     -   Azure Government regions
     -   Azure China regions
     -   US Department of Defense (DoD)
Power Apps Premium All Power Apps regions except the following:
     -   US Government (GCC)
     -   US Government (GCC High)
     -   China Cloud operated by 21Vianet
     -   US Department of Defense (DoD)
Power Automate Premium All Power Automate regions except the following:
     -   US Government (GCC)
     -   US Government (GCC High)
     -   China Cloud operated by 21Vianet
     -   US Department of Defense (DoD)
Contact
Name Support
Email support@bigdata.com
Connector Metadata
Publisher RAVENPACK INTERNATIONAL SL.
Website https://bigdata.com
Privacy Policy https://bigdata.com/privacy-policy
Categories AI;Data

BigData MCP Server - Client Guide

Welcome to the BigData MCP Server! This service provides AI assistants with powerful tools to access financial data, company information, and business intelligence through the Model Context Protocol (MCP).

🚀 Available Tools

1. Search News & Financial Content (bigdata_search)

Search across financial documents, earnings transcripts, news articles, analyst reports, SEC filings, and business content from thousands of sources.

Use Cases:

  • Research company developments and market trends
  • Find earnings call transcripts and analyst reports
  • Discover news articles about specific companies or sectors
  • Access SEC filings and regulatory documents
  • Search your private uploaded files

Parameters:

  • search_text (required): Your search query in natural language
    • Example: "Apple iPhone sales Q4 2024"
    • Example: "Tesla manufacturing expansion"
  • max_chunks (optional, default: 10): Maximum number of text excerpts to return (1-100)
    • Recommended: 20-50 for comprehensive research

What You Get:

  • Relevant text chunks from various documents
  • Source attribution with publication dates
  • Direct URLs to original documents
  • Timestamps for all content

Best Practices:

  • Run multiple searches with different queries to build comprehensive understanding
  • Start broad, then narrow down based on initial results
  • Always cite sources when using information from retrieved documents

2. Find Companies (find_companies)

Look up companies by name, ticker symbol, ISIN, CUSIP, or SEDOL to get their unique identifier and metadata.

Use Cases:

  • Convert company names to standardized identifiers
  • Look up ticker symbols
  • Find company sector and industry information
  • Required first step before using other company-specific tools

Parameters:

  • query (required): Company name, ticker, or identifier
    • Example: "Apple"
    • Example: "AAPL"
    • Example: "US0378331005" (ISIN)

What You Get:

  • RavenPack entity ID (needed for other tools)
  • Company name and ticker symbol
  • Sector and industry classification
  • Country of incorporation
  • Multiple identifiers (ISIN, CUSIP, SEDOL)

Important:

  • Always run this tool FIRST when starting research on a company
  • Use the returned entity ID for bigdata_tearsheet and bigdata_events_calendar

3. Generate Company Tearsheet (bigdata_tearsheet)

Get a comprehensive financial analysis report for any public company, aggregating data from 11 different sources.

Use Cases:

  • Comprehensive financial analysis
  • Investment research and due diligence
  • Understanding company financial health
  • Analyst consensus and price targets
  • Earnings analysis

Parameters:

  • rp_entity_id (required): RavenPack entity identifier from find_companies
    • Example: "4A6F00"

What You Get:

Company Overview:

  • Business description and key executives
  • Sector, industry, and headquarters location
  • Current stock price and market capitalization
  • Trading volume and metrics

Financial Position:

  • Balance sheet (assets, liabilities, equity, debt)
  • Key metrics (ROE, ROA, free cash flow yield)
  • Financial ratios (P/E, P/B, debt ratios, liquidity)

Operating Performance:

  • Income statement (revenue, expenses, profitability, EPS)
  • Cash flow statement (operating, investing, financing)

Analyst Coverage:

  • Buy/Sell recommendations and consensus
  • Price targets (high, low, consensus, median)
  • Forward revenue and EPS estimates (next 8 quarters)
  • Latest earnings surprise data

Workflow:

  1. First, call find_companies to get the entity ID
  2. Then, call this tool with the entity ID
  3. Optionally, use bigdata_search for recent news to supplement

4. Get Corporate Events Calendar (bigdata_events_calendar)

Retrieve upcoming and past corporate events including earnings calls and conference calls for specific companies.

Use Cases:

  • Plan ahead for earnings announcements
  • Track conference call schedules
  • Historical event analysis
  • Investment timing decisions

Parameters:

  • rp_entity_id (optional): List of RavenPack entity identifiers
    • Example: ["4A6F00", "D8442A"]
    • Leave empty to get all available events

What You Get:

  • Upcoming earnings call dates and times
  • Past event history
  • Conference call schedules
  • Event types and details
  • Organized by company

Workflow:

  1. First, call find_companies to get entity IDs
  2. Then, call this tool with a list of entity IDs

🔄 Typical Workflows

Research a Company

1. find_companies("Tesla")
   → Get entity ID: "4A6F00"

2. bigdata_tearsheet(rp_entity_id="4A6F00")
   → Get comprehensive financial data

3. bigdata_search("Tesla manufacturing expansion 2024", max_chunks=30)
   → Get recent news and developments

4. bigdata_events_calendar(rp_entity_id=["4A6F00"])
   → Check upcoming earnings dates

Industry Analysis

1. find_companies("Apple") → entity_id_1
   find_companies("Microsoft") → entity_id_2
   find_companies("Google") → entity_id_3

2. bigdata_tearsheet(rp_entity_id=entity_id_1)
   bigdata_tearsheet(rp_entity_id=entity_id_2)
   bigdata_tearsheet(rp_entity_id=entity_id_3)
   → Compare financial metrics

3. bigdata_search("tech sector AI investments Q4 2024", max_chunks=50)
   → Get industry trends and analysis

Earnings Preview

1. find_companies("Meta")
   → Get entity ID

2. bigdata_events_calendar(rp_entity_id=[entity_id])
   → Check when earnings call is scheduled

3. bigdata_tearsheet(rp_entity_id=entity_id)
   → Get analyst estimates and previous performance

4. bigdata_search("Meta Q4 2024 earnings preview", max_chunks=40)
   → Get analyst commentary and expectations

🔐 Authentication

The MCP server uses OAuth 2.0 for secure authentication. This ensures your data and queries remain protected while providing seamless access to BigData tools.

OAuth Flow

  1. Initial Connection: Your AI assistant or MCP client initiates a connection to the BigData MCP server
  2. Authorization Request: If not already authenticated, you'll be redirected to the BigData login page
  3. User Login: Enter your BigData credentials (email and password)
  4. Authorization Grant: After successful login, BigData issues an OAuth token
  5. Token Exchange: Your client receives the token and uses it for all subsequent requests
  6. Automatic Renewal: Tokens are automatically refreshed as needed

What You Need to Know

  • First-time setup: You'll need to authenticate once when connecting your AI assistant
  • Secure by design: OAuth tokens are encrypted and expire after a set period
  • No credential sharing: Your password is never shared with the AI assistant
  • Session management: Tokens are managed automatically by your MCP client

💡 Best Practices

Search Strategy

  • Start broad, then narrow: Begin with general queries, refine based on results
  • Use multiple searches: Different queries reveal different aspects
  • Specify timeframes naturally: "last quarter", "Q4 2024", "yesterday"
  • Combine terms: Include company names, topics, and timeframes

Source Attribution

  • Always cite sources: Include source name and date for all information
  • Link to originals: Provide URLs when available
  • Create a sources section: List all referenced documents at the end

Quota Management

  • Search efficiently: Use appropriate max_chunks values (20-50 recommended)
  • Reuse entity IDs: Don't call find_companies multiple times for the same company
  • Batch requests: Get tearsheets for multiple companies in sequence

🆘 Common Questions

Q: How do I get financial data for a company? A: First call find_companies with the company name, then use the returned entity ID with bigdata_tearsheet.

Q: What's the difference between search and tearsheet? A: Search finds articles and documents; tearsheet provides structured financial data (income statement, balance sheet, analyst ratings).

Q: Can I search my own uploaded files? A: Yes! The bigdata_search tool includes content from your private uploaded files.

Q: How recent is the data? A: Search results include timestamps. Tearsheet data is updated regularly with the latest quarterly reports and real-time stock prices.

Q: What if I don't know the company ticker? A: Just use the company name with find_companies - it will find the right company and provide all identifiers.

📞 Support

For questions, issues, or feature requests, please contact your BigData account representative or visit our support portal.

Throttling Limits

Name Calls Renewal Period
API calls per connection 100 60 seconds

Actions

Bigdata.com MCP endpoint

Bigdata.com MCP entry point

Bigdata.com MCP endpoint

Operation ID:
InvokeServer

Bigdata.com MCP entry point

Returns