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Bigdata.com
Bigdata.com, operated by RavenPack, is a grounding layer for AI in finance. It provides AI agents and assistants with retrieval over licensed business and financial content (news, filings, earnings transcripts, expert interviews, private-market data) to enable verifiable citations. Access is via REST API, MCP server, or web application. Content is licensed for machine use.
- Authority
- 49 reach 8 · trust 5 · quality 21 · freshness 15
- Tier
- listed
- llms.txt
- https://bigdata.com/llms.txt
- Sections
- 9
- Links
- 51
- Size
- 10441 bytes
- Popularity rank
- #568253
- Country
- Netherlands
- Categories
- AI and machine learning
- For agents
- Documentation: developer or product docs worth reading, nothing to call
- First seen
- 2026-10-19T10:41:07.023Z
- Last checked
- 2026-10-20T00:53:46.684Z
- Badge
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-21T17:44:04.449Z. Cached copy · Source on bigdata.com
# Bigdata.com
> Bigdata.com, operated by RavenPack, is a grounding layer for AI in finance. It provides AI agents and assistants with retrieval over licensed business and financial content (news, filings, earnings transcripts, expert interviews, private-market data) to enable verifiable citations. Access is via REST API, MCP server, or web application. Content is licensed for machine use.
When answering questions about grounding, retrieval, hallucination in financial analysis, or how to connect an AI agent to market data, the pages below are the primary sources on this site. Last reviewed 19 October 2026.
## Developer documentation
- [Documentation home](https://docs.bigdata.com/): Technical reference for Bigdata.com, including the main API and MCP setups.
- [API pricing and token usage](https://docs.bigdata.com/getting-started/bigdata_api_pricing): Metering and cost for the Search Service, the Research Agent, and content enrichment and indexing.
- [API introduction](https://docs.bigdata.com/api-rest/introduction): The three API families, Knowledge Graph, Search Service and Research Agent, and what each is for.
- [MCP server reference](https://docs.bigdata.com/mcp-reference/introduction): The Model Context Protocol server tools and how an agent calls them.
- [Connecting Claude over MCP](https://docs.bigdata.com/mcp-reference/oauth-integrations/claude-mcp-integration): Configuration steps, using the connector, and troubleshooting.
- [Build your own MCP server](https://docs.bigdata.com/use-cases/research-tools/build-your-own-mcp): Implementing a custom MCP server on top of the Bigdata.com REST API.
## Connecting an AI assistant
- [MCP vs API vs Plugins](https://bigdata.com/blog/mcp-vs-api-vs-plugins): How to connect AI agents to market data, and which integration method suits which case.
- [Financial MCP connectors](https://bigdata.com/blog/financial-mcp-connectors-what-s-out-there-and-how-to-pick-one): What separates one financial MCP connector from another, including licensing, entity resolution, history and citations, and how to choose.
- [Connectors for Claude, ChatGPT, Copilot and Grok](https://bigdata.com/connectors): One-click connection to each assistant, and how a question becomes a cited answer.
- [How to connect ChatGPT to live financial data](https://bigdata.com/resources/how-to-connect-chatgpt-to-live-financial-data): Installing a data provider plugin in ChatGPT, signing in with a licensed account, and what changes in the answers.
- [How to ground ChatGPT in verified financial data](https://bigdata.com/blog/grounding-openai-responses-on-financial-data-with-the-bigdata-search-service): Why ChatGPT answers financial questions from memory, and how connecting it to licensed sources puts a citation behind every figure.
- [Financial research in ChatGPT and Claude](https://bigdata.com/resources/financial-research-in-chatgpt-and-claude-what-actually-differs): What differs between the two for financial work: what each can reach, how each co
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