Platform capability · operational API · OpenAPI & MCP tooling
Laboratory API & MCP Integrations
Connect Flask Track to internal applications, laboratory automation,
reporting pipelines, AI agents, robotics, and external business systems.
Programmatically manage biological records, create operational work,
inspect schedules, complete protocol steps, retrieve execution data,
and run reporting workflows through organization-scoped interfaces.
Bring Flask Track into the rest of your infrastructure
Laboratory operations rarely exist in a single application. Flask Track
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.
⚙️
Operational Automation
Create records, retrieve execution context, inspect schedules,
complete supported steps, and coordinate repeatable laboratory
processes programmatically.
📊
Reporting Pipelines
Discover available reports, connect analytical consumers,
and incorporate Flask Track 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 Flask Track
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
Flask Track publishes an interactive OpenAPI interface describing
available routes, request bodies, authentication requirements,
parameters, and response structures.
MCP tooling for governed AI operations
Flask Track 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 Flask Track
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 Flask Track to
dashboards, scheduled reporting jobs, data consumers, and broader
analytical infrastructure.
Service users for accountable machine access
API keys are associated with service users: dedicated machine identities
that can be assigned organization roles and governed separately from
human accounts.
🤖
Dedicated Machine Identities
Operate integrations through named service users instead
of shared human credentials or anonymous system access.
🔑
Managed API Credentials
Issue, review, expire, revoke, and replace credentials
independently for each integration or automation service.
🛡️
Compliance-Aware Actions
Service users remain subject to organization roles,
certification requirements, approval rules, and restricted
operational actions.
🧾
Auditable Machine Activity
Attribute changes to the service user, credential,
organization, request context, and affected operational
records.
Organization-scoped authentication
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
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✔ Connect internal applications, automation services, robotics,
dashboards, and external operational systems
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✔ Read structured species, ingredient, tool, plasmid, protocol,
workflow, sample, and batch records
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✔ Create supported operational records through validated,
organization-scoped routes
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✔ Retrieve sample events and inspect generated batch and sample schedules
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✔ Complete supported protocol steps and submit execution timestamps
programmatically
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✔ Discover reusable reports for dashboards, BI tools, and analytical pipelines
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✔ Authenticate with managed service users and organization API keys
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✔ Connect compatible AI agents through structured MCP tooling
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✔ Generate clients and integrations from an evolving OpenAPI specification
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✔ Preserve permission checks, compliance rules, rate limits,
and audit attribution for machine activity
Programmatic access without surrendering operational control
Flask Track 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.