KynticAI Discovery MCP
Understand the shape of a workflow without sending KynticAI the real customer records.
Discovery MCP runs inside an AI workspace the buyer already controls. It can inspect approved metadata such as system types, field categories and outcome names. The buyer reviews that description first and, if they choose, shares a metadata-only Discovery Signature that KynticAI can use to build a synthetic demonstration with made-up data.
Why this helps
The buyer can show KynticAI enough to understand the problem without sharing the underlying operational records.
That makes the first technical conversation much more concrete. KynticAI can see what kinds of systems and fields are involved, while the buyer can inspect exactly what is being shared before anything leaves its own environment.
The IT manager runs discovery locally in a workspace they already trust.
The Discovery Signature contains metadata only and is reviewed before it is shared.
The first KynticAI demo uses synthetic equivalent data rather than the customer's real operational records.
Five steps from local discovery to a possible private pilot.
Run Discovery MCP inside your own AI workspace
LocalUse KynticAI Discovery MCP from Codex, Claude, Cursor or another MCP-compatible environment. It looks at the metadata you approve inside your own workspace rather than asking you to upload customer records to KynticAI.
Review what it found before sharing anything
ReviewCheck the types of source systems, connectors, fields, outcome labels, data freshness and any governance notes. You decide whether the description is safe and useful before it leaves your environment.
Approve a metadata-only Discovery Signature
ApproveThe Discovery Signature describes the shape of the workflow and data. It must not contain passwords, credentials, source rows, raw exports, prompt packages or local logs.
KynticAI builds a synthetic version of the same pattern
DemoKynticAI uses the approved metadata description to build a demonstration with made-up data and similar kinds of systems. This lets the buyer see the proposed workflow without sending the real operational records to KynticAI.
Decide whether a Fortress pilot or Elite rollout discussion is worthwhile
NextIf the synthetic demonstration shows something useful, the next step can be a clearly scoped Fortress pilot. Elite is the route for larger executive and organisational rollout discussions where appropriate.
Example Discovery Signature
The buyer approves a description of the data, not the data itself.
This is an illustrative example. Discovery MCP is designed to return safe metadata categories, governance notes and demonstration preferences. Do not send passwords, credentials, raw exports, source rows, support message bodies, prompt packages, local logs or raw customer records through public KynticAI routes.
01 / Run locally
Describe the workflow inside the buyer's own environment
workspace = buyer-approved AI environment
targetWorkflow = prioritise next sales action
sourceSystemFamilies = CRM + web analytics + product analytics + billing metadata
02 / Review the description
Approve only safe metadata
signatureVersion = kynticai.discovery-signature.v1
safeMetadataFields = stageField + eventNameField + conversionNameField + observedAtField
forbiddenDataConfirmed = true
03 / Build a demonstration
Use made-up data that mirrors the same kind of workflow
approvedForSyntheticDemoBuild = true
closestSyntheticDomain = professional-services
nextStep = synthetic demo -> Fortress pilot scope -> Elite walkthrough where approved
What happens after the synthetic demo
A good demonstration should make the real next step easier to scope.
KynticAI uses the approved Discovery Signature to build a synthetic example around similar kinds of systems and fields. The buyer can then decide whether there is enough value to justify testing the real workflow inside an agreed customer-controlled environment.
Private runtime pilot
Fortress pilot
If the synthetic demonstration shows that the workflow is worth testing, move to a scoped Fortress pilot with the relevant system types, customer data boundary, deployment approach and result format already understood.
View FortressLarger organisation rollout
Elite route
Use Elite when the discussion needs to cover the complete organisational route: discovery, synthetic demonstration, private Fortress deployment, approved local model options and how results will be reviewed over time.
View EliteThe same approach can be used to describe very different kinds of workflow.
Discovery works best when the system types, decision owner, security boundary and result the buyer wants to explore are specific enough to build a meaningful synthetic example.
B2B SaaS Sales
Describe the relevant CRM, website, product, support and billing metadata so KynticAI can build a synthetic sales-action example without receiving the real customer records.
Ecommerce Basket
Describe basket, product, conversion, delivery, discount and support metadata so a synthetic version of the customer journey can be demonstrated.
Support Retention
Use ticket category, entitlement, usage, account stage and renewal-window metadata to shape a potential Fortress retention pilot.
Healthcare Operations
Use non-clinical rota, bed-flow, equipment, transport and supply metadata categories to build synthetic operational examples only.
Recruitment Matching
Describe role, availability, skills, stage and outcome metadata without transferring candidate records.
Finance Operations
Describe service, product, retention and workflow metadata for operational examples without making regulated financial-advice claims.
Bring the shape of the workflow. Keep the sensitive records in your own environment.
Describe the workflow, types of source system and what you want the demonstration to show. Do not send secrets, credentials, raw exports, source rows, support bodies, prompt packages, local logs or raw customer records through the public form.