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Create Custom Integration

createCustomIntegration

Create a custom integration type (team-level catalog entry) that users can then connect as user-provided MCP connections. Requires manager-or-above role.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
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.
server_urlYes
auth_methodYes
oauth_client_idNo
oauth_client_secretNo

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already signal readOnly=false, idempotent=false, and destructive=false, so the write behavior is known. The description adds valuable behavioral context beyond annotations: the created entity is a team-level catalog entry, the operation requires manager-or-above permissions, and users will later connect it as an MCP connection. This is meaningful for an agent deciding whether to call the tool.

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, dense sentence with no filler or repetition. The verb and resource are front-loaded, and the role requirement is appended without bloating the text. Every part earns its place.

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

Completeness3/5

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

The description is sufficient to understand the high-level purpose and permission requirement, but it does not cover parameter dependencies such as when oauth_client_id and oauth_client_secret are needed, nor does it clarify the server_url/auth_method semantics. With no output schema and only 17% schema description coverage, the definition is minimally viable but has clear gaps.

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

Parameters2/5

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

Schema description coverage is only 17%, with team_id carrying the sole description. The tool description does not explain server_url, auth_method, oauth_client_id, oauth_client_secret, or how they relate to each other. Since the schema leaves most parameters undescribed, the description needed to compensate but does not.

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 states a specific action ('Create'), a specific resource ('custom integration type'), and adds a clarifying parenthetical ('team-level catalog entry') that distinguishes it from a concrete connection. The follow-up clause about users connecting them as user-provided MCP connections makes the tool's purpose unmistakable and separates it from sibling tools like createConnection.

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 context: this creates a reusable catalog entry rather than an actual connection, and it requires a manager-or-above role. It does not explicitly name alternatives or say 'when not to use', but the catalog-vs-connection framing provides enough guidance for an agent to select it appropriately.

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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