Power Automate Governance with FlowStudio MCP Classify, tag, and govern Power Automate flows at scale through the FlowStudio MCP cached store — without Dataverse, without the CoE Starter Kit, and without the Power Automate portal. This skill uses update_store_flow to write governance metadata and the monitoring tools ( list_store_flows , get_store_flow , list_store_makers , etc.) to read tenant state. For monitoring and health-check workflows, see the flowstudio-power-automate-monitoring skill. Start every session with tools/list to confirm tool names and parameters. This skill covers workflows and patterns — things tools/list cannot tell you. If this document disagrees with tools/list or a real API response, the API wins. Critical: How to Extract Flow IDs list_store_flows returns id in format . . You must split on the first . to get environmentName and flowName for all other tools: id = "Default-." environmentName = "Default-" (everything before first ".") flowName = "" (everything after first ".") Also: skip entries that have no displayName or have state=Deleted — these are sparse records or flows that no longer exist in Power Automate. If a deleted flow has monitor=true , suggest disabling monitoring ( update_store_flow with monitor=false ) to free up a monitoring slot (standard plan includes 20). The Write Tool: update_store_flow update_store_flow writes governance metadata to the Flow Studio cache only — it does NOT modify the flow in Power Automate. These fields are not visible via get_live_flow or the PA portal. They exist only in the Flow Studio store and are used by Flow Studio's scanning pipeline and notification rules. This means: ownerTeam / supportEmail — sets who Flow Studio considers the governance contact. Does NOT change the actual PA flow owner. rule_notify_email — sets who receives Flow Studio failure/missing-run notifications. Does NOT change Microsoft's built-in flow failure alerts. monitor / critical / businessImpact — Flow Studio classification only. Power Automate has no equivalent fields. Merge semantics — only fields you provide are updated. Returns the full updated record (same shape as get_store_flow ). Required parameters: environmentName , flowName . All other fields optional. Settable Fields Field Type Purpose monitor bool Enable run-level scanning (standard plan: 20 flows included) rule_notify_onfail bool Send email notification on any failed run rule_notify_onmissingdays number Send notification when flow hasn't run in N days (0 = disabled) rule_notify_email string Comma-separated notification recipients description string What the flow does tags string Classification tags (also auto-extracted from description

hashtags

) businessImpact string Low / Medium / High / Critical businessJustification string Why the flow exists, what process it automates businessValue string Business value statement ownerTeam string Accountable team ownerBusinessUnit string Business unit supportGroup string Support escalation group supportEmail string Support contact email critical bool Designate as business-critical tier string Standard or Premium security string Security classification or notes Caution with security : The security field on get_store_flow contains structured JSON (e.g. {"triggerRequestAuthenticationType":"All"} ). Writing a plain string like "reviewed" will overwrite this. To mark a flow as security-reviewed, use tags instead. Governance Workflows 1. Compliance Detail Review Identify flows missing required governance metadata — the equivalent of the CoE Starter Kit's Developer Compliance Center. 1. Ask the user which compliance fields they require (or use their organization's existing governance policy) 2. list_store_flows 3. For each flow (skip entries without displayName or state=Deleted): - Split id → environmentName, flowName - get_store_flow(environmentName, flowName) - Check which required fields are missing or empty 4. Report non-compliant flows with missing fields listed 5. For each non-compliant flow: - Ask the user for values - update_store_flow(environmentName, flowName, ...provided fields) Fields available for compliance checks: Field Example policy description Every flow should be documented businessImpact Classify as Low / Medium / High / Critical businessJustification Required for High/Critical impact flows ownerTeam Every flow should have an accountable team supportEmail Required for production flows monitor Required for critical flows (note: standard plan includes 20 monitored flows) rule_notify_onfail Recommended for monitored flows critical Designate business-critical flows Each organization defines their own compliance rules. The fields above are suggestions based on common Power Platform governance patterns (CoE Starter Kit). Ask the user what their requirements are before flagging flows as non-compliant. Tip: Flows created or updated via MCP already have description (auto-appended by update_live_flow ). Flows created manually in the Power Automate portal are the ones most likely missing governance metadata. 2. Orphaned Resource Detection Find flows owned by deleted or disabled Azure AD accounts. 1. list_store_makers 2. Filter where deleted=true AND ownerFlowCount > 0 Note: deleted makers have NO displayName/mail — record their id (AAD OID) 3. list_store_flows → collect all flows 4. For each flow (skip entries without displayName or state=Deleted): - Split id → environmentName, flowName - get_store_flow(environmentName, flowName) - Parse owners: json.loads(record["owners"]) - Check if any owner principalId matches an orphaned maker id 5. Report orphaned flows: maker id, flow name, flow state 6. For each orphaned flow: - Reassign governance: update_store_flow(environmentName, flowName, ownerTeam="NewTeam", supportEmail="new-owner@contoso.com") - Or decommission: set_store_flow_state(environmentName, flowName, state="Stopped") update_store_flow updates governance metadata in the cache only. To transfer actual PA ownership, an admin must use the Power Platform admin center or PowerShell. Note: Many orphaned flows are system-generated (created by DataverseSystemUser accounts for SLA monitoring, knowledge articles, etc.). These were never built by a person — consider tagging them rather than reassigning. Coverage: This workflow searches the cached store only, not the live PA API. Flows created after the last scan won't appear. 3. Archive Score Calculation Compute an inactivity score (0-7) per flow to identify safe cleanup candidates. Aligns with the CoE Starter Kit's archive scoring. 1. list_store_flows 2. For each flow (skip entries without displayName or state=Deleted): - Split id → environmentName, flowName - get_store_flow(environmentName, flowName) 3. Compute archive score (0-7), add 1 point for each: +1 lastModifiedTime within 24 hours of createdTime +1 displayName contains "test", "demo", "copy", "temp", or "backup" (case-insensitive) +1 createdTime is more than 12 months ago +1 state is "Stopped" or "Suspended" +1 json.loads(owners) is empty array [] +1 runPeriodTotal = 0 (never ran or no recent runs) +1 parse json.loads(complexity) → actions < 5 4. Classify: Score 5-7: Recommend archive — report to user for confirmation Score 3-4: Flag for review → Read existing tags from get_store_flow response, append #archive-review update_store_flow(environmentName, flowName, tags=" #archive-review") Score 0-2: Active, no action 5. For user-confirmed archives: set_store_flow_state(environmentName, flowName, state="Stopped") Read existing tags, append #archived update_store_flow(environmentName, flowName, tags=" #archived") What "archive" means: Power Automate has no native archive feature. Archiving via MCP means: (1) stop the flow so it can't run, and (2) tag it

archived

so it's discoverable for future cleanup. Actual deletion requires the Power Automate portal or admin PowerShell — it cannot be done via MCP tools. 4. Connector Audit Audit which connectors are in use across monitored flows. Useful for DLP impact analysis and premium license planning. 1. list_store_flows(monitor=true) (scope to monitored flows — auditing all 1000+ flows is expensive) 2. For each flow (skip entries without displayName or state=Deleted): - Split id → environmentName, flowName - get_store_flow(environmentName, flowName) - Parse connections: json.loads(record["connections"]) Returns array of objects with apiName, apiId, connectionName - Note the flow-level tier field ("Standard" or "Premium") 3. Build connector inventory: - Which apiNames are used and by how many flows - Which flows have tier="Premium" (premium connector detected) - Which flows use HTTP connectors (apiName contains "http") - Which flows use custom connectors (non-shared_ prefix apiNames) 4. Report inventory to user - For DLP analysis: user provides their DLP policy connector groups, agent cross-references against the inventory Scope to monitored flows. Each flow requires a get_store_flow call to read the connections JSON. Standard plans have ~20 monitored flows — manageable. Auditing all flows in a large tenant (1000+) would be very expensive in API calls. list_store_connections returns connection instances (who created which connection) but NOT connector types per flow. Use it for connection counts per environment, not for the connector audit. DLP policy definitions are not available via MCP. The agent builds the connector inventory; the user provides the DLP classification to cross-reference against. 5. Notification Rule Management Configure monitoring and alerting for flows at scale. Enable failure alerts on all critical flows: 1. list_store_flows(monitor=true) 2. For each flow (skip entries without displayName or state=Deleted): - Split id → environmentName, flowName - get_store_flow(environmentName, flowName) - If critical=true AND rule_notify_onfail is not true: update_store_flow(environmentName, flowName, rule_notify_onfail=true, rule_notify_email="oncall@contoso.com") - If NO flows have critical=true: this is a governance finding. Recommend the user designate their most important flows as critical using update_store_flow(critical=true) before configuring alerts. Enable missing-run detection for scheduled flows: 1. list_store_flows(monitor=true) 2. For each flow where triggerType="Recurrence" (available on list response): - Skip flows with state="Stopped" or "Suspended" (not expected to run) - Split id → environmentName, flowName - get_store_flow(environmentName, flowName) - If rule_notify_onmissingdays is 0 or not set: update_store_flow(environmentName, flowName, rule_notify_onmissingdays=2) critical , rule_notify_onfail , and rule_notify_onmissingdays are only available from get_store_flow , not from list_store_flows . The list call pre-filters to monitored flows; the detail call checks the notification fields. Monitoring limit: The standard plan (FlowStudio for Teams / MCP Pro+) includes 20 monitored flows. Before bulk-enabling monitor=true , check how many flows are already monitored: len(list_store_flows(monitor=true)) 6. Classification and Tagging Bulk-classify flows by connector type, business function, or risk level. Auto-tag by connector: 1. list_store_flows 2. For each flow (skip entries without displayName or state=Deleted): - Split id → environmentName, flowName - get_store_flow(environmentName, flowName) - Parse connections: json.loads(record["connections"]) - Build tags from apiName values: shared_sharepointonline → #sharepoint shared_teams → #teams shared_office365 → #email Custom connectors → #custom-connector HTTP-related connectors → #http-external - Read existing tags from get_store_flow response, append new tags - update_store_flow(environmentName, flowName, tags=" #sharepoint #teams") Two tag systems: Tags shown in list_store_flows are auto-extracted from the flow's description field (e.g. a maker writes

operations

in the PA portal description). Tags set via update_store_flow(tags=...) write to a separate field in the Azure Table cache. They are independent — writing store tags does not touch the description, and editing the description in the portal does not affect store tags. Tag merge: update_store_flow(tags=...) overwrites the store tags field. To avoid losing tags from other workflows, read the current store tags from get_store_flow first, append new ones, then write back. get_store_flow already has a tier field (Standard/Premium) computed by the scanning pipeline. Only use update_store_flow(tier=...) if you need to override it. 7. Maker Offboarding When an employee leaves, identify their flows and apps, and reassign Flow Studio governance contacts and notification recipients. 1. get_store_maker(makerKey="") → check ownerFlowCount, ownerAppCount, deleted status 2. list_store_flows → collect all flows 3. For each flow (skip entries without displayName or state=Deleted): - Split id → environmentName, flowName - get_store_flow(environmentName, flowName) - Parse owners: json.loads(record["owners"]) - If any principalId matches the departing user's OID → flag 4. list_store_power_apps → filter where ownerId matches the OID 5. For each flagged flow: - Check runPeriodTotal and runLast — is it still active? - If keeping: update_store_flow(environmentName, flowName, ownerTeam="NewTeam", supportEmail="new-owner@contoso.com") - If decommissioning: set_store_flow_state(environmentName, flowName, state="Stopped") Read existing tags, append #decommissioned update_store_flow(environmentName, flowName, tags=" #decommissioned") 6. Report: flows reassigned, flows stopped, apps needing manual reassignment What "reassign" means here: update_store_flow changes who Flow Studio considers the governance contact and who receives Flow Studio notifications. It does NOT transfer the actual Power Automate flow ownership — that requires the Power Platform admin center or PowerShell. Also update rule_notify_email so failure notifications go to the new team instead of the departing employee's email. Power Apps ownership cannot be changed via MCP tools. Report them for manual reassignment in the Power Apps admin center. 8. Security Review Review flows for potential security concerns using cached store data. 1. list_store_flows(monitor=true) 2. For each flow (skip entries without displayName or state=Deleted): - Split id → environmentName, flowName - get_store_flow(environmentName, flowName) - Parse security: json.loads(record["security"]) - Parse connections: json.loads(record["connections"]) - Read sharingType directly (top-level field, NOT inside security JSON) 3. Report findings to user for review 4. For reviewed flows: Read existing tags, append #security-reviewed update_store_flow(environmentName, flowName, tags=" #security-reviewed") Do NOT overwrite the security field — it contains structured auth data Fields available for security review: Field Where What it tells you security.triggerRequestAuthenticationType security JSON "All" = HTTP trigger accepts unauthenticated requests sharingType top-level "Coauthor" = shared with co-authors for editing connections connections JSON Which connectors the flow uses (check for HTTP, custom) referencedResources JSON string SharePoint sites, Teams channels, external URLs the flow accesses tier top-level "Premium" = uses premium connectors Each organization decides what constitutes a security concern. For example, an unauthenticated HTTP trigger is expected for webhook receivers (Stripe, GitHub) but may be a risk for internal flows. Review findings in context before flagging. 9. Environment Governance Audit environments for compliance and sprawl. 1. list_store_environments Skip entries without displayName (tenant-level metadata rows) 2. Flag: - Developer environments (sku="Developer") — should be limited - Non-managed environments (isManagedEnvironment=false) — less governance - Note: isAdmin=false means the current service account lacks admin access to that environment, not that the environment has no admin 3. list_store_flows → group by environmentName - Flow count per environment - Failure rate analysis: runPeriodFailRate is on the list response — no need for per-flow get_store_flow calls 4. list_store_connections → group by environmentName - Connection count per environment 10. Governance Dashboard Generate a tenant-wide governance summary. Efficient metrics (list calls only): 1. total_flows = len(list_store_flows()) 2. monitored = len(list_store_flows(monitor=true)) 3. with_onfail = len(list_store_flows(rule_notify_onfail=true)) 4. makers = list_store_makers() → active = count where deleted=false → orphan_count = count where deleted=true AND ownerFlowCount > 0 5. apps = list_store_power_apps() → widely_shared = count where sharedUsersCount > 3 6. envs = list_store_environments() → count, group by sku 7. conns = list_store_connections() → count Compute from list data: - Monitoring %: monitored / total_flows - Notification %: with_onfail / monitored - Orphan count: from step 4 - High-risk count: flows with runPeriodFailRate > 0.2 (on list response) Detailed metrics (require get_store_flow per flow — expensive for large tenants): - Compliance %: flows with businessImpact set / total active flows - Undocumented count: flows without description - Tier breakdown: group by tier field For detailed metrics, iterate all flows in a single pass: For each flow from list_store_flows (skip sparse entries): Split id → environmentName, flowName get_store_flow(environmentName, flowName) → accumulate businessImpact, description, tier Field Reference: get_store_flow Fields Used in Governance All fields below are confirmed present on the get_store_flow response. Fields marked with * are also available on list_store_flows (cheaper). Field Type Governance use displayName * string Archive score (test/demo name detection) state * string Archive score, lifecycle management tier string License audit (Standard vs Premium) monitor * bool Is this flow being actively monitored? critical bool Business-critical designation (settable via update_store_flow) businessImpact string Compliance classification businessJustification string Compliance attestation ownerTeam string Ownership accountability supportEmail string Escalation contact rule_notify_onfail bool Failure alerting configured? rule_notify_onmissingdays number SLA monitoring configured? rule_notify_email string Alert recipients description string Documentation completeness tags string Classification — list_store_flows shows description-extracted hashtags only; store tags written by update_store_flow require get_store_flow to read back runPeriodTotal * number Activity level runPeriodFailRate * number Health status runLast ISO string Last run timestamp scanned ISO string Data freshness deleted bool Lifecycle tracking createdTime * ISO string Archive score (age) lastModifiedTime * ISO string Archive score (staleness) owners JSON string Orphan detection, ownership audit — parse with json.loads() connections JSON string Connector audit, tier — parse with json.loads() complexity JSON string Archive score (simplicity) — parse with json.loads() security JSON string Auth type audit — parse with json.loads(), contains triggerRequestAuthenticationType sharingType string Oversharing detection (top-level, NOT inside security) referencedResources JSON string URL audit — parse with json.loads()