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Duvo MCP

by io.github.duvoai

Create Clarity Landscape Node

createClarityLandscapeNode

Create an area folder in the process tree. An active area (the default) requires organization admin+; a "proposal" area may be added by any organization member.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
orgIdYes
parentIdNo
ownerLabelNo
descriptionNoOne or two sentences saying what family of work this area groups. Persisted as the area's summary.
creationModeNoUse "proposal" to add an area for review instead of asserting it exists. A proposal is idempotent: an equivalent live area under the same parent is returned untouched rather than duplicated. Defaults to "active" — except in a landscape-onboarding chat, which may only propose, and so defaults to "proposal".

Schema Changelog

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

  1. Changed2 schema fields changed
    • removedInput schema / properties / creationMode / default
      Removed value: -"active"
    • changedInput schema / properties / creationMode / description
      Previous value: -"Use \"proposal\" to add an area for review instead of asserting it exists. A proposal is idempotent: an equivalent live area under the same parent is returned untouched rather than duplicated."New value: +"Use \"proposal\" to add an area for review instead of asserting it exists. A proposal is idempotent: an equivalent live area under the same parent is returned untouched rather than duplicated. Defaults to \"active\" — except in a landscape-onboarding chat, which may only propose, and so defaults to \"proposal\"."
  2. First observed

TDQS

B3.2/5.0
Behavior3/5

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

The description adds useful context beyond the sparse annotations by disclosing that active areas require organization admin+ while proposals are open to any member. However, it does not disclose side effects, return behavior, or the idempotency nuance described in the creationMode schema.

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?

The description is a single, front-loaded sentence with no filler. It packs the core purpose and key permission distinction into minimal space.

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

Completeness2/5

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

With six parameters, no output schema, and weak annotations, the description is too thin to be complete. It lacks guidance on parent/owner fields, sibling alternatives, and what the tool returns or how creation is confirmed.

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

Parameters3/5

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

The description partially compensates for the low 33% schema coverage by explaining the creationMode distinction and its permission implications. However, it adds no meaning for parentId or ownerLabel, and name/orgId remain only schema-defined, so the description does not fully carry the parameter-semantics burden.

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

Purpose4/5

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

The description clearly states a specific verb ('Create'), resource ('area folder'), and location ('in the process tree'), which distinguishes it from sibling tools like createClarityFolder or createClarityProcessNode. It does not explicitly name a sibling, so it stops short of the clearest possible differentiation.

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

Usage Guidelines2/5

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

The description gives a permission-based distinction between 'active' and 'proposal' areas but does not explain when to prefer this tool over alternatives such as createClarityFolder or updateClarityLandscapeNode. No explicit when-to-use or when-not-to-use guidance is provided.

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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