Standard Metrics Unveils AI-Powered Solution to Cut Board Meeting Prep from Hours to Minutes

San Francisco, CA – Standard Metrics, a leading financial data and analytics platform for venture capital firms and their portfolio companies, has launched a new Model Context Protocol (MCP) server designed to dramatically reduce the time investors spend preparing for board meetings. John Melas-Kyriazi, Co-founder and CEO of Standard Metrics, announced the innovation via social media, highlighting its ability to unify disparate data sources and provide instant, board-ready insights through natural language prompts.

"Investors: imagine cutting board meeting prep from hours to minutes with one prompt," stated John Melas-Kyriazi in a recent tweet. He emphasized the new system's capability to leverage their MCP server to "unify information across Standard Metrics, Notion, Google Calendar, and other tools with a simple prompt, reducing board meeting prep and other admin to minutes."

The core of this advancement is Standard Metrics' new MCP server, which connects artificial intelligence models like Anthropic's Claude directly to a firm's critical data. This allows investors to query their portfolio performance, financial metrics, and other crucial data using conversational language. The system can, for instance, search Google Calendar for company names, find corresponding performance data in Standard Metrics, and then generate a quick performance summary, even updating platforms like Notion as requested.

This integration addresses a significant pain point for venture capitalists, automating tasks that traditionally involve manual data aggregation and analysis across multiple platforms. The MCP server provides secure, permission-aware access to a wide array of data within Standard Metrics, including company information, financial metrics (revenue, growth, burn rate), budgets, forecasts, custom data, documents, notes, and fund-level details.

The Model Context Protocol (MCP) is an open standard introduced by Anthropic in mid-2024, enabling large language models (LLMs) to securely connect with external tools and live enterprise data. This broader industry trend aims to enhance AI accuracy and personalization by providing real-time, context-specific information, moving from traditional tool-driven workflows to more intuitive, conversation-driven interactions. Standard Metrics' adoption of MCP positions it at the forefront of this shift within the financial technology sector.

Standard Metrics plans to continue evolving its AI offerings. According to a company announcement, "This release is just step one. We plan to continue to improve on our customers’ AI experiences with Standard Metrics data via additional data streams to external LLMs and and improving the experience of our in-app AI portfolio analyst." This strategic direction underscores the company's commitment to leveraging AI for increased efficiency and deeper insights in the private markets.