Open-source MPI solutions give you full control over patient matching and zero licensing fees, at the price of your team owning the operational story. For FHIR-first stacks in 2026, the open-source landscape has matured to the point where it is a viable choice for serious production deployments, not just a research-grade fallback.
This list covers the five open-source MPI solutions worth knowing for a FHIR stack. For the rest of the FHIR series, the broader catalog covers the surrounding ecosystem.
For the architectural ground first, the complete guide to FHIR master patient index in 2026 covers what an MPI in a FHIR context actually needs to do.
The 5 Open-Source MPI Solutions Worth Knowing
Order tracks adoption in real FHIR-stack deployments.
- JEMPI. The OpenHIE community's FHIR-native MPI, with deterministic and probabilistic matching. Active development, real-world deployment in global-health settings.
- OpenMPI (OpenHIE). Older OpenHIE MPI, predecessor to JEMPI, still in production in some lower-resource deployments.
- SantéMPI. Open-source MPI from the SanteSuite project, used in Caribbean and African health information exchange deployments.
- HAPI FHIR MDM module. HAPI's built-in Master Data Management module, suitable for teams that already run HAPI as their FHIR backend.
- Mirth Match. Open-source matching engine from the Mirth (NextGen Connect) lineage, often used alongside other open-source integration components.
What Open-Source MPI Gives You That Commercial Doesn't
Three things tend to drive teams toward open-source:
- Cost predictability. Zero licensing fees, full source code access, no vendor lock-in.
- Customization depth. You can modify matching logic, integrate with custom data sources, and tune thresholds without going through a vendor support process.
- Community support. Healthy open-source MPI projects have communities that respond to issues and contribute fixes faster than vendor support cycles.
The five above clear these bars to varying degrees. JEMPI and HAPI MDM lead on community activity in 2026.
Which Solution for Which FHIR Stack
Global-health and lower-resource deployments often go to JEMPI or SantéMPI because of the OpenHIE community lineage. Teams already running HAPI FHIR usually add the HAPI MDM module rather than introducing a separate MPI tool. Mirth-heavy integration shops add Mirth Match to their existing pipeline.
For the broader FHIR-native MPI market including commercial options, the Top 5 FHIR-native MPI products for 2026 covers the full picture.
For the explicit comparison between sides, commercial vs open-source MPI: how to choose walks through the trade-offs case by case.
What to Watch Out For
The cost story for open-source MPI shows up six months in, when your team realizes that tuning the matching threshold, handling new source-system integrations, and responding to clinical-safety questions all land on your engineers rather than a vendor. If that workload fits your team's capacity, open-source wins on flexibility. If not, the conversation tilts back toward commercial.
How to Run an Open-Source MPI Pilot
Load a realistic slice of your patient data into the candidate solution, configure deterministic and probabilistic matching for your data shape, and measure precision-recall at varying thresholds. Then have your operations team try the match-resolution tooling for a sample of unsure cases. The candidate that performs well on both fronts is the one to short-list.
Anything that requires significant custom code to integrate with your FHIR stack is one to think twice about.
