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Duvo MCP

by io.github.duvoai

Mark Notification Batch Read

markNotificationBatchRead
Idempotent

Mark every unread live member of a notification batch as read for the authenticated user. Pass types to narrow the mark-read to those member types, and severity (exact) or minSeverity (threshold, mutually exclusive with severity) to narrow it by urgency — e.g. the page's active filters; omit them to mark every live member. Narrowing matters when the batch card was rendered under a filter: the rows marked read should be the rows the card counted. Returns the count of members that were updated. Requires the Notification Center feature; returns 404 when it is not enabled for the team or the batch does not exist or belongs to another recipient/team.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe notification batch's unique identifier
typesNo
team_idNoDuvo team UUID to operate on. API keys are pinned to a single team — omit this (it falls back to the key's team) or pass that same team; a different team is rejected. OAuth callers, who can span multiple teams, should pass the target team here.
severityNo
minSeverityNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • changedInput schema / properties / types / items / enum
      Previous value: -[
-  "connection_broken",
-  "case_failed",
-  "critical_case_issue",
-  "case_issue",
-  "critical_eval_issue",
-  "eval_issue",
-  "job_issue",
-  "job_done",
-  "background_job",
-  "schedule_issue"
-]New value: +[
+  "connection_broken",
+  "case_failed",
+  "critical_case_issue",
+  "case_issue",
+  "critical_eval_issue",
+  "eval_issue",
+  "job_issue",
+  "job_done",
+  "background_job",
+  "schedule_issue",
+  "config_proposal"
+]
    • changedInput schema / properties / types / maxItems
      Previous value: -10New value: +11
  2. Changed2 schema fields changed
    • changedInput schema / properties / types / items / enum
      Previous value: -[
-  "connection_broken",
-  "critical_eval_issue",
-  "eval_issue",
-  "job_issue",
-  "job_done",
-  "background_job",
-  "schedule_issue"
-]New value: +[
+  "connection_broken",
+  "case_failed",
+  "critical_case_issue",
+  "case_issue",
+  "critical_eval_issue",
+  "eval_issue",
+  "job_issue",
+  "job_done",
+  "background_job",
+  "schedule_issue"
+]
    • changedInput schema / properties / types / maxItems
      Previous value: -7New value: +10
  3. Changed2 schema fields changed
    • changedInput schema / properties / types / items / enum
      Previous value: -[
-  "connection_broken",
-  "job_issue",
-  "eval_issue",
-  "job_done",
-  "background_job",
-  "schedule_issue"
-]New value: +[
+  "connection_broken",
+  "critical_eval_issue",
+  "eval_issue",
+  "job_issue",
+  "job_done",
+  "background_job",
+  "schedule_issue"
+]
    • changedInput schema / properties / types / maxItems
      Previous value: -6New value: +7
  4. First observed

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare this as a mutating, idempotent, non-destructive operation. The description adds meaningful behavior beyond that: it affects only 'unread live members,' explains that filters should mirror the page's active filters, states that it returns the count of updated members, and discloses the feature requirement plus 404 conditions. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, each earning its place: main action, filter semantics, the rationale for narrowing, and error/return behavior. The most important information is front-loaded, and there is no redundant repetition of schema content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having no output schema, the description tells the agent the return value ('count of members that were updated') and the 404 failure modes (feature not enabled, batch not found, or wrong recipient/team). For a mutating batch operation with five parameters, this covers all critical information needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 40% (only id and team_id have descriptions). The description compensates by explaining the purpose of `types` (narrow by member types), the exact-vs-threshold semantics of `severity` vs `minSeverity`, their mutual exclusivity, and the default behavior when omitted. This adds meaning well beyond the bare enum lists in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Mark every unread live member of a notification batch as read for the authenticated user.' It precisely defines the operation's scope ('unread live member', 'notification batch'), which clearly distinguishes it from siblings like markNotificationRead (single notification) and markAllNotificationsRead (all notifications), even without naming them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear parameter-level guidance: pass `types` to narrow by member type, use `severity` (exact) or `minSeverity` (threshold, mutually exclusive) to narrow by urgency, and omit them to mark every live member. It also explains when narrowing matters ('when the batch card was rendered under a filter'). However, it does not explicitly state when to choose this tool over the sibling markNotificationRead or markAllNotificationsRead, so the routing context is strong but alternatives aren't named.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.1/5.0
Disambiguation2/5

Despite detailed descriptions, many tool names are highly ambiguous, with multiple tools covering the same conceptual actions (e.g., acceptClarityCaptureSuggestion vs. acceptClarityTeamAssignmentSuggestion, or the many deleteClarity*Interview tools). The set is so large that distinguishing between, say, listClarityFolders, listClarityProcesses, and listClarityProcessSummaries requires reading deep into descriptions, reducing agent selection accuracy.

Naming Consistency4/5

The naming convention is predominantly verb_noun (e.g., createClarityProcess, listAgents, deleteQueue), and is remarkably consistent across the 316 tools. There are only minor deviations, such as 'fileSuggestedClarityProcesses' (verb + adjective noun) and 'bulkUpdateCasePriority' (where 'bulk' could be seen as a prefix), but overall the pattern holds strongly.

Tool Count1/5

With 316 tools, this server is extremely oversized for any single agent to manage effectively. The massive number of tools suggests poor modularization—many of these tools likely belong in separate, smaller servers focused on specific domains (e.g., Clarity, Pulse, Agent management). The cognitive load for an agent to choose from 316 options is very high, leading to frequent misselection.

Completeness4/5

The tool surface covers an extraordinarily wide range of operations across the Duvo platform: agents, runs, cases, queues, Clarity processes, skills, integrations, notifications, teams, and more. Most resource types have full CRUD and lifecycle management. Notable minor gaps exist (e.g., no tools for managing specific notification batch severities dynamically, and some interview management is missing batch operations), but for the platform's scope, coverage is impressively thorough.

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