GLG MCP Connector Brings Expert Insights into AI Workflows

GLG, the expert-network platform, on Wednesday launched a Model Context Protocol (MCP) connector that lets clients feed its research into the AI tools they already use. The move is the latest attempt to bridge qualitative human expertise with machine-learning workflows, a gap that has left much of GLG's call-note and content library sitting outside the agentic systems many finance and consulting teams now run.

The connector works as a query layer. Users can search their own project call history and pull from GLG's Expert Content Library directly inside an AI chatbot or research agent. Every answer traces back to a specific expert conversation or piece of content, which matters for compliance. GLG said compliance officers keep full control over what data enters the AI tool.

CEO Gemma Postlethwaite framed the product as part of a longer bet. "Artificial intelligence can expand access to human intelligence, and unlock more of its true value," she said in the release. Chief Product Officer John Londono called the connector a way to "eliminate friction at every step of the research lifecycle."

The launch lands at a moment when large asset managers and consultancies are racing to embed proprietary research into AI copilots. Most have struggled to combine structured data with the kind of judgment calls that live in interview notes and panel transcripts. GLG's bet is that its compliance framework and curated expert base give it an edge over generic retrieval-augmented generation tools that lack source-level attribution.