Fragmentum builds album — the open-source platform that makes scientific tools reproducible, shareable, and now AI-orchestrable. Born in research. Built for scale.
Researchers waste time fighting tooling instead of doing science. Industry loses money on pipelines that can't reproduce.
Album solves the reproducibility crisis in scientific computing. Wrap any existing code into a versioned, shareable solution file. Run it anywhere — full data ownership guaranteed.
From a single laptop to HPC clusters and cloud deployments — album handles the complexity so researchers and teams don't have to.
Host your solution catalog on any Git platform — GitLab, GitHub, or self-hosted. No central registry, no lock-in. Full data sovereignty.
Each solution defines its own conda environment with locked dependencies. Install once, reproduce exactly — across any platform.
Wrap solutions in Python, R, Java, Kotlin, C++, and more. One unified registry for heterogeneous tool stacks.
Findable, Accessible, Interoperable, Reproducible. Built-in support for FAIR research data principles and regulatory traceability.
Deploy via Docker, Singularity, or natively on HPC clusters. Same solution definition, zero reconfiguration across environments.
Sync and async REST endpoints, Python SDK, and CLI. Integrate album into existing platforms, LIMS, or orchestration layers in hours.
album-mcp brings the Model Context Protocol to album — enabling AI agents to discover, install, compose, and execute scientific solutions through natural language. 16 tools. One protocol. Full lifecycle.
AI agents search across all connected catalogs, inspect solution arguments and metadata, and find the right tool for the task — no CLI memorization needed.
The AI scaffolds multi-step pipelines, wires persistent data paths between steps, generates complete solution code, validates against the RDF schema, and deploys — all autonomously.
TOTP-based authentication gates every destructive operation — install, run, deploy, remove. Enterprise-grade security for AI-driven scientific workflows.
album-mcp doesn't just execute — it authors. The AI generates scaffold code, writes lifecycle functions (run, install, test), assembles valid solution files, and publishes to catalogs. Solutions creating solutions.
Every album operation — from catalog management to solution authoring — exposed as a standardized MCP tool that any AI agent can invoke.
A three-step workflow that scales from a single laptop to cloud infrastructure — with AI orchestration built in.
Package any existing tool into a versioned album solution file with its own environment spec. Push to your Git-hosted catalog.
One command provisions the exact conda environment. Colleagues reproduce your workflow by pointing to the same catalog and version.
Connect album-mcp. Your AI assistant discovers solutions, chains them into pipelines, generates new solution code, validates metadata, and deploys — all through natural language.
Album is already used across leading research institutions and scientific communities worldwide.
As AI transforms research workflows, the need for standardized, reproducible, AI-orchestrable tool infrastructure is exploding — and no one owns this layer yet.
Established user base in microscopy, cryo-ET, and cell biology. Expanding into pharma, genomics, and clinical research pipelines.
Album is domain-agnostic by design. The same framework works for climate science, materials research, financial modeling, and data engineering.
Open-source core with premium managed catalog hosting, enterprise SSO, audit logging, SLA-backed support, and hosted album-mcp orchestration.
Install album in seconds. Open source, MIT licensed. Works on Linux, macOS, and Windows.
Album is backed by published research. If you use it in your work, please cite: