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Glama

Duvo MCP

by io.github.duvoai

List Integrations

listIntegrations
Read-onlyIdempotent

List the team's integration catalog: built-in integration types plus any custom connection types defined for the team. OAuth authorization flows are browser-based and cannot be performed via this API; use the Duvo dashboard to complete OAuth-based connections.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNo
limitNo
offsetNo
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.

Schema Changelog

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

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already establish read-only, idempotent, non-destructive behavior, so the description does not need to repeat those. It adds the meaningful caveat that OAuth authorization cannot be performed here. However, it does not disclose pagination behavior, ordering, or response structure, which would be useful given no output 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 two tight sentences with no filler. The purpose is front-loaded, and the OAuth caveat is placed second where it naturally supports invocation decisions.

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 covers what the tool returns conceptually and warns about the OAuth limitation. But with no output schema and poor parameter documentation for 'type', an agent cannot fully understand filtering behavior. Since all parameters are optional, a valid call is still possible, but the ambiguity leaves a clear gap.

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 25%, and the tool description does not compensate. The 'type' parameter is completely undocumented in both the schema and description, leaving its allowed values ambiguous. Limit and offset are self-explanatory, and team_id is well-described in the schema, but the low coverage and missing 'type' semantics hurt agent confidence.

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 the verb-resource pair ('List the team's integration catalog') and enumerates what is included: built-in integration types and custom connection types. It is specific enough to distinguish from more generic list tools, though it does not explicitly contrast with siblings like listConnections or listRevisionIntegrations.

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 an explicit when-not-to-use directive: OAuth flows cannot be performed via this API and the Duvo dashboard should be used instead. This is concrete usage guidance, though it does not address when to prefer this tool over other integration-related list tools.

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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