We’re launching the Latch MCP and announcing its availability within Claude Science, Anthropic’s new AI workbench for scientists. AI for biology requires agent-native infrastructure: systems where agents can store, process, and visualize large molecular datasets from the interfaces scientists already use. Biological analysis workflows often require substantial compute. Retries or incorrect long-running tool calls can quickly inflate workflow time and cost, especially when analyses take hours or days to complete. These tools should also be curated with appropriate parameters and agent-readable documentation, ideally provided by the original assay developer, to support correct use across many complex scientific contexts. At Latch, we’ve seen customers of our Solution Provider partners, including TakaraBio, Vizgen, and AtlasXOmics, use both the Latch Agent and external harnesses like Claude Code and Cursor to accelerate analysis of their data. The Latch MCP is a remote MCP server that securely connects agent harnesses to the Latch platform, giving agents access to verified bioinformatics tools built and maintained by kit and instrument providers. Agents can navigate data on Latch and launch existing deployments of validated bioinformatics workflows to analyze that data.

This is the year of agents in biology. What you're seeing in code is already unfolding in molecular data analysis, reorganizing workflows in basic research and drug development. Path forward is focused benchmarking + engineering scoped to specific types of assays. Just as coding agents had to reliably write JavaScript before they could build a browser, biology agents must first learn to accurately process and interpret concrete measurements, (eg. spatial assays), before they can reason about disease, drug mechanism, or patient response. Our roadmap reflects this progression: procedural skill in analysis -> emergent biological reasoning -> synthesis across data types, translational context, and realistic ambiguity. Towards systems that can eventually support expensive, high-stakes decisions in drug programs or research projects. Diffusion in biology is slower than software and needs to be thought through carefully. We work directly with the teams building measurement tech (eg. TakaraBio and Vizgen) and package assay-specific agents alongside their kits and instruments. Scientists complete sample preparation, then use these tech-specific agents to move from raw data to answers and figures. Our partners white-label our platform; we do not run a direct biotech sales motion. Now hiring rapidly across major assay categories, prioritized by which we believe will contribute most to the area under the molecular data curve over the next several years - Spatial - Single Cell - Epigenomics - Genomics - Perturbation/Screening - Diagnostics Looking for talented scientists and engineers with strong foundations in theory and deep experience in these areas to help us build scientifically accurate agents.