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Duvo MCP

by io.github.duvoai

Create Slack Channel Trigger

createAgentSlackTrigger

Create a Slack channel trigger on an agent (Agent in the Duvo UI): the agent starts a Run whenever a matching message is posted in the channel. An agent can carry one trigger per channel, so call this once per channel. The Slack workspace must be installed for the team AND bound to the agent's live build first (see the Slack bound-workspaces endpoint) — otherwise this returns 400.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesThe agent's unique identifier
channel_idYesSlack channel ID to watch, e.g. `C0123ABCD`.
is_privateNoWhether the channel is private. Defaults to false. Private channels require the Duvo Slack app to be invited to the channel.
match_ruleYesWhich channel messages fire the trigger: `{"kind":"all"}` for every message, or `{"kind":"contains","values":["invoice"]}` to match keywords.
channel_nameYesSlack channel name shown in Duvo, without the leading `#`, e.g. `support-inbox`.
trigger_typeYesTrigger type. Only `slack_channel_message` (a message posted in a Slack channel) is supported here.
slack_team_idNoSlack workspace (team) ID the channel belongs to, e.g. `T0123ABCD`. Defaults to the team's default installed workspace. Discover the workspaces an agent can use with the bound-workspaces endpoint.
integration_instance_idNoSpecific bound Slack connection to run the trigger off. Omit to use your own connection, or pass one returned by the bound-workspaces endpoint.

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only convey read/write/idempotency/destructiveness flags. The description goes beyond them by explaining the trigger's side effect (a Run starts on matching messages), the one-trigger-per-channel limit, the binding prerequisite, and the 400 failure mode. This is substantial extra behavioral context.

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?

Three sentences carry all operative information with no filler: purpose/behavior, cardinality constraint, and prerequisite/failure. The most important scoping guidance is front-loaded.

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?

For an 8-parameter create operation with no output schema, the description covers what happens on success, the per-channel limitation, prerequisite setup, and the error condition, while the schema documents every parameter. There are no invocation requirements left unaddressed.

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 coverage is 100%, with each of the 8 parameters already described by name, format, defaults, and examples. The description reinforces the general matching and per-channel concepts but adds no parameter-specific semantics beyond the schema, so the baseline 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 Slack channel trigger on an agent' — and then defines the tool's effect as starting a Run when a matching message is posted. Naming 'Slack channel trigger' distinguishes it from sibling case-trigger tools such as createAgentCaseTrigger.

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?

It gives operational conditions: call once per channel, and only after the Slack workspace is installed and bound to the agent's live build, with a 400 failure otherwise. It doesn't explicitly contrast with alternatives like upsertAgentTrigger or updateSlackTrigger, so it stops short of full routing guidance.

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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