The Team
Built by researchers,
for researchers.
MedMCP is an agentic system that runs state-of-the-art medical imaging pipelines from a familiar chat interface. No terminal, no code, just plain language.
The Workspace
MedMCP runs as a self-contained workspace. A file browser, a built-in medical image viewer, a library of reusable pipelines, and an agent that ties them together.
Use plain language, the same way you'd explain it to a colleague. No commands, no parameters, no prior AI experience needed.
MedMCP selects the right tools, sequences them, and handles all the technical details automatically.
Before MedMCP touches your data, you see exactly what is about to happen. Approve or reject with a single click. You always stay in full control.
The Agentic System
MedMCP is an agent, not a chatbot. It reasons about your goal, sequences the right tools, executes them under your control, and keeps a complete record of everything it did.
From one plain-language goal, it sequences the whole chain (DICOM conversion, skull-stripping, registration, segmentation) in the correct order.
It orchestrates trusted, published methods. Nothing is generated at runtime. The intelligence plans; proven tools execute.
Every file operation and tool call is shown for review first. Nothing touches your data until you approve it.
Every approved and rejected action is logged to an append-only record: a complete, reproducible trail of what ran on your data and when.
Distill any session into a deterministic, replayable pipeline. Run it again on new patients with no model in the loop. The same steps every time.
Bind one workflow to a folder of subjects and process an entire cohort in a single run, with failures isolated per subject and progress streamed live.
Who It's For
In the clinic, the lab, or a clinical trial, MedMCP makes the field's best imaging tools available to the people who should use them.
Run validated segmentation, registration, and lesion analysis on your own patients.
Skip the Python environments and DICOM wrangling, and batch a whole cohort in one request.
Quantify imaging biomarkers across multi-site cohorts, with a full audit trail behind every result.
Privacy & Safety
MedMCP was designed for clinical and translational research environments, where data governance is non-negotiable.
The AI model runs on your hardware. No imaging data, patient metadata, or results are ever sent to a cloud service.
Every file operation, every analysis step, every tool call is shown to you before it runs. You stay in full control.
After installation, MedMCP does not need an active internet connection to run analyses.
Every approved and rejected action is logged persistently, giving you a complete record of what ran on your data and when.
Always Getting Better
MedMCP is built around open-weight models (Gemma 4 today). However, nothing ties it to a single model. As stronger open models are released, you can move to them and the whole system improves with no extra work on your side.
What requires a frontier cloud model today will soon run on your local hardware. MedMCP is built to make the most of each new generation.
The model and the tools stay separate. Your imaging pipelines are validated once and always behave the same way; a more capable model simply gets better at choosing and running them.
Our Vision
"The tools exist. The methods work. What is missing is the infrastructure to put them in the hands of the people who are best positioned to use them. MedMCP exists to close that gap."
We believe that one of the biggest problems in medical image analysis is the systamatic disconnect of well-working tools and people being unable to use them. No clinician or researcher should need a software engineer to run these pipelines. Our goal is simple: make the field's best methods usable by anyone who needs them, reliably and safely, on their own infrastructure.
Capability Stacks
MedMCP's capabilities are organized into domain stacks. Activate one and its tools appear automatically in the workspace, ready for the agent to plan with. New stacks land regularly.
Inspect, validate, and convert DICOM series to standard research formats. The foundation layer every other stack builds on.
Under developmentBrain extraction, white matter lesion segmentation, cortical thickness, and multi-modal registration for neurological research.
Under developmentCardiac structure segmentation and functional analysis for echocardiography and cardiac MRI workflows.
Coming soonCell detection, tissue segmentation, and quantification pipelines for digital pathology and microscopy images.
Coming soonThe Team
Get involved
MedMCP is in active development, and we're open to ideas, collaborations, and new use cases. Reach out for a demo, or just to talk through what you're working on and how it could be integrated.