The new server connects Claude, ChatGPT, Cursor, and other MCP-compatible clients to experiments, samples, inventory, and approvals inside Scispot.
KITCHENER, Ontario, March 19, 2026 /PRNewswire-PRWeb/ -- Scispot, the AI-native lab operating system for modern life science teams, today announced the availability of the Scispot MCP Server, a Model Context Protocol server that lets AI assistants securely read live lab context and take governed actions across experiments, samples, inventory, storage, and documentation inside Scispot. Scispot is built for high-throughput labs such as molecular diagnostics labs, CROs, and CDMOs, as well as AI-driven biotech companies where speed, traceability, and compliance must work together. Teams can run AI directly in production workflows without exporting data or breaking audit trails.
As AI use spreads across life science teams, most assistants still stop at drafts and summaries because they cannot safely act on the systems where lab work actually happens. Scispot MCP is designed to close that gap.
Model Context Protocol, or MCP, is an open standard for connecting AI clients to external tools and data. With Scispot's implementation, labs can connect the AI tools they already use - including Claude, ChatGPT, and developer tools like Cursor and Claude Code - to the same Scispot workspace their teams already rely on. Instead of working from copied data or disconnected scripts, AI agents can operate directly against governed lab systems through Scispot's existing permissions, approvals, and logging.
What the Scispot MCP Server enables
- Scientists and operators can ask operational questions, trace sample lineage, summarize runs, and update records without jumping between systems.
- Bioinformaticians and data teams can pull structured experiment data into analysis workflows without manual exports or CSV wrangling.
- Lab managers can review queues, utilization, backlog, and handoffs through conversational AI while keeping oversight of every action.
- Quality and compliance teams can let AI propose or execute approved changes while preserving approvals, traceability, and audit readiness.
The current release exposes 27 MCP tools across Scispot's Labsheets, Labspaces (ELN), Manifests, Freezer Manager, Labflows, and image retrieval. Labs can search and update Labsheets, read and write ELN content, link structured records to experiments and protocols, retrieve manifests and storage context, and work with sample and image data inside a single workspace.
Unlike generic AI connectors, every Scispot MCP action inherits user-level permissions and runs through the same audit trail as work performed in the Scispot UI. Sensitive actions can be routed through approval steps before changes are applied, and structured data remains the source of truth inside Scispot rather than in the AI client. This gives labs a practical way to add AI speed without weakening control, compliance, or data integrity.
"Life science teams do not need another AI demo that sits beside the lab. They need AI that can work inside the system that already governs samples, experiments, and approvals," said Satya Singh, CTO and Co-Founder of Scispot. "MCP gives us a standard way to connect the AI tools teams already use to live lab operations. The result is faster execution without giving up traceability, chain of custody, or control."
The Scispot MCP Server is available today to Scispot customers. Teams evaluating Scispot can request a demo and access details at www.scispot.com.
About Scispot:
Scispot is the AI-native lab operating system for modern biotech and diagnostics teams. Trusted by labs around the world, the platform unifies samples, experiments, inventory, instruments, workflows, and compliance in one audit-ready workspace, with 7,000+ app integrations and 250+ instrument connections through GLUE. Scispot supports drug discovery, contract testing, molecular diagnostics, pathology, biobanking, and other structured lab workflows. Learn more at www.scispot.com.
Media Contact
Cody Boekestyn, Scispot, 1 2503004875, [email protected], www.scispot.com
SOURCE Scispot
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