Integration layer · OpenAPI · MCP · service automation
Build on top of the laboratory platform
Connect internal software, automation, robotics, reporting services, AI agents, and business systems to the same
operational model your laboratory uses interactively.
FlaskTrack exposes organization-scoped interfaces for scientific records, execution, schedules, reporting, and
controlled machine access so integration extends the platform instead of bypassing it.
Versioned recordsProtocols, scientific entities, files, and controlled
releases
Live executionScheduled work, batches, samples, roles, and operational events
Instrument dataLocal ingestion, mapping, provenance, review, and downstream
use
Data pipelinesSQL, reports, Python/R transforms, APIs, and analytical storage
Built-in governancePermissions, signatures, audit history, review, and validation
support
Bring FlaskTrack into the rest of your infrastructure
Laboratory operations rarely exist in a single application. FlaskTrack
provides structured programmatic access so approved systems can exchange
operational data without bypassing organization boundaries, authorization
rules, validation, or audit attribution.
🔌
System Integrations
Connect internal applications, LIMS and ERP systems,
laboratory interfaces, inventory services, and external
operational tools.
Reporting Pipelines
Discover available reports, connect analytical consumers,
and incorporate FlaskTrack data into dashboards, scheduled
exports, and downstream reporting workflows.
🤖
Agents & MCP Clients
Give approved AI clients a structured tool surface for
retrieving context and performing permitted FlaskTrack
operations through governed machine identities.
Manage operational biology programmatically
The API exposes structured laboratory records and execution context,
allowing external systems to participate in daily operations instead
of functioning only as passive data exports.
🧬
Catalog & Reference Records
Retrieve species, ingredients, tools, plasmids, protocols,
workflows, and other structured reference data required by
connected systems.
🧫
Samples & Batches
Create operational records, retrieve sample or batch details,
resolve identifiers, and connect external systems to active
laboratory work.
📅
Schedules & Execution Context
Inspect generated batch and sample schedules so dashboards,
alerts, automation services, and operators can act on the
same execution plan.
✅
Step Completion & Actions
Complete supported protocol steps and submit operational
actions from approved systems while retaining timestamps,
actor attribution, and validation.
🧾
Events & Execution History
Retrieve recorded sample events, execution metadata,
timestamps, notes, and linked operational entities for
synchronization and analysis.
👥
Organization Users
Retrieve active organization users when connected tools
need to resolve ownership, responsibility, assignments,
or human attribution.
OpenAPI-based integration
FlaskTrack publishes an interactive OpenAPI interface describing
available routes, request bodies, authentication requirements,
parameters, and response structures.
Typed Request & Response Schemas
Use documented JSON structures to generate clients,
validate payloads, and reduce ambiguity between connected
applications.
🛠️
Client Generation
Use the OpenAPI specification with compatible code
generators, testing tools, API clients, and integration
development workflows.
📈
Continuously Expanding Surface
The FlaskTrack API evolves alongside the platform.
The live OpenAPI documentation remains the authoritative
reference for currently available operations.
FlaskTrack also provides Model Context Protocol tooling that maps
approved platform capabilities into structured tools for compatible
AI clients and agent environments.
Structured Agent Tools
Allow compatible agents to discover supported operations
as defined tools instead of relying on unstructured browser
automation or direct database access.
🔗
Backed by the API Surface
MCP operations connect to the same evolving FlaskTrack
capabilities represented through the platform’s structured
API and OpenAPI definitions.
🛡️
Permission-Aware Execution
Agent actions remain subject to the service user’s role,
organization context, compliance restrictions, and available
API permissions.
🔍
Reviewable Machine Activity
Distinguish machine-driven activity from human activity
and retain the actor, credential, request context, and
affected records for review.
Automate execution without bypassing the operator
Connected systems can assist with execution, data capture, and
synchronization while human operators remain responsible for laboratory
judgment, exception handling, and production decisions.
📋
Retrieve the Current Schedule
Load batch or sample schedules into operator interfaces,
robotics systems, dashboards, and alerting services.
📥
Submit Execution Data
Record supported actions and completion information from
connected equipment or applications rather than requiring
duplicate manual entry.
⏱️
Preserve Actual Completion Times
Submit supported completion timestamps so historical records
represent when work occurred, not merely when a synchronized
request reached the platform.
⚠️
Respect Operational Restrictions
API-driven execution remains subject to record state,
validation, role permissions, compliance controls, and
action-specific authorization.
Programmatic reporting and analytical access
Use the API to discover reusable reports and connect FlaskTrack to
dashboards, scheduled reporting jobs, data consumers, and broader
analytical infrastructure.
API keys are associated with service users: dedicated machine identities
that can be assigned organization roles and governed separately from
human accounts.
API requests use organization-aware authentication so each request
is evaluated within the correct tenant, identity, and permission context.
🏢
Organization Context
Requests identify the target organization using the
x-organization header.
🔐
API Key Authentication
Authenticate machine requests using the
x-api-key header and a managed organization
credential.
👤
Session Authentication
Supported API operations may also be accessed through
authorized user sessions where appropriate.
🚦
Rate-Limited Access
Requests are rate limited per authenticated user or API key
to protect availability and reduce uncontrolled integration
traffic.
Currently documented API areas
The API documentation currently includes operations across the following
platform areas. Available routes continue to expand, so integrations
should use the live OpenAPI documentation as the source of truth.
🧬
Catalogs
Species, ingredients, tools, plasmids, protocols,
and workflows.
🧫
Operational Records
Samples, sample lookups, batches, sample events,
and record details.
📅
Scheduling
Generated schedules for samples and batches, including
workflow execution context.
📊
Reports & Users
Organization report discovery and active user lookup
for connected applications.
Built for practical integration workflows
✔ Connect internal applications, automation services, robotics,
dashboards, and external operational systems
✔ Read structured species, ingredient, tool, plasmid, protocol,
workflow, sample, and batch records
✔ Create supported operational records through validated,
organization-scoped routes
✔ Retrieve sample events and inspect generated batch and sample schedules
✔ Complete supported protocol steps and submit execution timestamps
programmatically
✔ Discover reusable reports for dashboards, BI tools, and analytical pipelines
✔ Authenticate with managed service users and organization API keys
✔ Connect compatible AI agents through structured MCP tooling
✔ Generate clients and integrations from an evolving OpenAPI specification
✔ Preserve permission checks, compliance rules, rate limits,
and audit attribution for machine activity
Buyer evaluation
Plan the integration before committing to automation
The API is most valuable when ownership, authorization, failure handling, and audit
expectations are decided before production use.
01
Integration scope
Identify the records and actions that genuinely need programmatic access instead of exposing the
entire operating model at once.
02
Accountability
Assign service identities, API-key ownership, rotation procedures, request attribution, and
incident-response responsibilities.
03
Change management
Test integrations against the live OpenAPI specification and plan for version changes, retries,
validation failures, and downstream outages.
Programmatic access without surrendering operational control
FlaskTrack gives approved systems meaningful access to laboratory
operations while preserving human responsibility, organization isolation,
service-user accountability, validation, compliance-aware authorization,
and auditable execution history.
