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Agentic AI · MCP Servers

MCP Servers for Lab Instruments

QPillars builds production-grade Model Context Protocol (MCP) servers for laboratory instruments. Vendor-neutral, AI-safety-aware, ready for Claude, Copilot, OpenAI Agents SDK, and any MCP-compatible agent. Built on shipped instrument-control work - two delivered references and one open-source contribution to the SiLA 2 ecosystem (openapi-to-sila2 on PyPI).

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What You Get

A complete MCP server build, productized into a fixed-price 6-week engagement.

Production-Grade MCP Servers

We build MCP (Model Context Protocol) servers that wrap instrument SDKs - serial, TCP, REST, gRPC, vendor-proprietary - and expose typed tools any AI agent can invoke. Schema validation, error handling, observability, and audit trails included.

Vendor-Neutral by Design

Generic MCP shops build for SaaS APIs. We build for physical instruments. The same MCP server works with Claude, GPT, Microsoft Copilot, OpenAI Agents SDK, CrewAI, LangGraph - whichever AI client your team or your customers use.

AI-Safety + Human-in-the-Loop

Every destructive operation requires explicit human approval. Configurable safety policies. Pre-tool-call validation against a digital-twin state model. Plan simulation before any physical move. Designed for regulated lab environments.

4-8 Week Delivery, Fixed Price

AI-Ready Instrument engagement: production MCP server + reference integration with your AI client of choice + API hardening report + branded demo asset. Six weeks, fixed price. We scope the work in a 30-minute technical call with the founder before any contract.

What our clients say

“
What impressed me the most about them is their passion to deliver good products. QPillars has been an integral part of our team - their deep understanding of instrument software has been transformative for our product development.

Dr. Andreas Frutiger

VP of R&D, Lino Biotech AG

“
Their rapid understanding of our needs, agile way of working, and communication stood out. They delivered exactly what we needed - reliable, well-engineered software for our LigandTracer instruments.

Jos Buijs

CEO, Ridgeview Instruments AB

Frequently Asked Questions

An MCP (Model Context Protocol) server is a service that exposes capabilities (tools, resources, prompts) to AI agents via a standard protocol. MCP is open, backed by Anthropic, and supported across all major agent frameworks. For laboratory instruments, an MCP server is the bridge between an instrument's vendor SDK and an AI agent that wants to operate it.
Without one, every AI agent that wants to control your instrument has to integrate with your custom SDK directly - locking you to one vendor, one programming language, one error model. With an MCP server, any MCP-compatible AI client (Claude, Microsoft Copilot, OpenAI agents, custom Python agents) can discover and operate your instrument with zero re-integration. It is the universal interface for the AI-agent era.
Generic MCP shops build for SaaS APIs - their developers have never written instrument-control software. We have. The patterns we apply (digital-twin state validation, pre-tool-call hooks, plan simulation, async event channels, idempotency, audit trail) come from shipped instrument-control work, not from generic dev experience. Two delivered references (Lino Biotech, Ridgeview Instruments) and one open-source contribution (openapi-to-sila2) back this up.
All MCP-compatible clients. As of 2026 that includes Claude Desktop, Claude Code, Microsoft Copilot Studio, OpenAI Agents SDK, CrewAI, LangGraph, AG2, PydanticAI, and any custom Python or TypeScript agent. The MCP server is vendor-neutral by design - choose your AI client, change your AI client later, the server stays the same.
REST, gRPC, GraphQL, SiLA 2 (we ship the openapi-to-sila2 generator on PyPI under Apache 2.0), vendor SDKs we evaluate per engagement (major liquid-handler, plate-reader, and chromatography SDKs on request), USB / RS-232 / GPIB / CAN, and proprietary serial protocols when needed. The MCP layer abstracts whatever the instrument speaks underneath.
Our AI-Ready Instrument engagement delivers a complete production MCP server in six weeks against a fixed price. Larger custom scopes (multi-instrument, complex async workflows, regulatory submissions) run 8-12 weeks. We always start with a 30-minute technical call with the founder to scope honestly before the engagement. Request a one-pager for full pricing.
Architecturally yes - we build with audit trails, electronic-signature support, immutable timestamps, role-based access, and pre-tool-call validation by default. Validation evidence for FDA / IEC 62304 / 21 CFR Part 11 / IVDR is your QMS work; we provide the architecture, the documentation, and the validation impact assessments. We have shipped this pattern on a clinical-grade IVD platform.

Have an instrument API? Let's build an MCP server.

Send us your API spec or vendor SDK documentation. We will scope the MCP server in 1 week, fixed-price - then ship in 6.

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