Duvo MCP

Create Automation

createAutomation

Create a new automation. Its first agent is created alongside it so the caller lands on something editable. On a team on revision semantics the automation holds a single draft revision and no live revision, with the agent's default build bound into that draft, and the first activation makes the draft revision 1; on any other team the automation is a bare container and the build stands on its own.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes	Human-readable automation name.
`team_id`	No	Duvo 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.

Schema Changelog

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

AddedSep 2, 2026

TDQS

A4.2/5.0

Behavior5/5

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

Even with annotations already indicating this is a mutating, non-idempotent operation, the description adds substantial behavioral disclosure: the first agent is auto-created, the revision/draft lifecycle is explained, the default build is bound into the draft, first activation promotes to revision 1, and non-revision teams get a bare container. This is exactly the kind of side-effect detail that agents cannot infer from 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?

Two sentences carry the core action up front and then pack necessary behavioral nuance into a dense but efficient second sentence. There is no filler, and the conditional structure clearly separates revision-semantics teams from all others.

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

Completeness4/5

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

The description is behaviorally complete for the two team scenarios and covers the side effects of creation. It does not mention what the caller receives back (e.g., the created automation's ID), which would be helpful given there is no output schema, but the schema and annotations cover most remaining operational needs.

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?

Schema description coverage is 100%, with both name and team_id already well documented in the input schema. The tool description adds no parameter-specific meaning beyond what the schema provides, so the baseline of 3 is appropriate.

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 ('Create a new automation') and adds that the first agent is created alongside it, which clearly distinguishes it from related create tools like createAgent. The added behavioral detail makes the tool's purpose unmistakable even among a large sibling set.

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

Usage Guidelines3/5

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

The description provides rich context about how the tool behaves on teams with revision semantics versus other teams, which helps a caller set expectations. However, it never explicitly names alternatives such as createAgent for standalone agent creation or updateAutomation for modifying an existing automation, so when-to-use versus alternatives is only implied.

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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