Benchling utilizes Model Context Protocol to bridge scientific data with AI ecosystems. Published. April 30, 2026 Benchling has launched AI Connectors, a new integration suite built on the Model Context Protocol (MCP) designed to unify fragmented scientific and enterprise data streams. The platform, which supports over 1,300 biotech organizations including Merck and Moderna, aims to eliminate the manual "copy-paste" workflows that currently plague R&D. By establishing a standardized interface, the connectors allow researchers to pull context directly from institutional tools like SharePoint, Snowflake, and Notion into their experimental records. This bidirectional data flow ensures that AI agents can access the full breadth of a project's history - ranging from experiment records to internal institutional knowledge - without losing critical scientific context. The new capabilities also extend to specialized research tools, allowing scientists to query a deep index of over 8 million biomedical papers via Elicit and GXL without leaving their digital notebooks. Furthermore, the Benchling MCP Server enables external AI models, such as Claude and ChatGPT, to query structured laboratory records directly, providing researchers with answers grounded in verified experimental data. By integrating bioinformatics workflows from Seqera and large datasets via Amazon S3, the update seeks to turn Benchling into a centralized hub for the entire R&D lifecycle. Following a successful beta phase, the company expects general availability of the full MCP offering in May 2026.

Seqera acquires Tinybio to democratize access to ai-powered bioinformatics.