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  • InSync”able” AI Infrastructure | Unified MCP-Ready Data for LLMs
AI infrastructure

InSync MCP

InSync’s MCP bridges the gap between LLMs and our unified data foundation of proprietary estimates, actuals and guidance through secure, structured data access. Our MCP layer provides systematic querying protocols that allow AI applications to efficiently extract relevant information from InSync’s deep fundamental dataset without system overload into instant, accurate analysis. The result: AI agents bypass time-consuming data generation and focus on what matters—producing deep, accurate, actionable insights for our clients at speed.

  • Market-Leading Speed & Coverage : The fastest, most comprehensive MCP available—13+ tools-giving you instant access to everything you need
  • Smart Query Optimization : Dynamic tool calling and intelligent query planning work together to enhance performance and retrieve data in milliseconds.
  • Integrate into your LLMs : Deploy our InSync MCP server using streamable HTTP Protocol with a link/URL
  • Currently Supported Integrations : Claude; ChatGPT; Gemini; VS Code; Cursor
  • Industry Standard Authentication : OAuth 2.1. when configuring the server connection
  • Data with more KPIs than any Other Provider : Actuals, consensus, and guidance; macro-economic indicators; commodities; weather data; and unstructured company data all in one place
Demo InSync MCP
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The InSync”able”AI Infrastructure

Power your LLMs and Chatbots with the industry’s first and only unified database with:

  • A direct, structural link between every reported actual and its corresponding consensus estimate metric
  • Robust, user-friendly proprietary taxonomy making it easier and faster to map, query, and analyze at scale
  • An Model Context Protocol (MCP) ready dataset, which can deliver an immediate, AI-powered integrated fundamental and quantitative analysis which other fragmented platforms cannot
  • Seamlessly access InSync’s deep proprietary structured data and curated unstructured datasets via MCP
  • A larger dataset reduces hallucinations and enables the execution of more complex prompt handling

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