nc-mcp-server

create_conversation

Start a Nextcloud Talk conversation as one-to-one, group, or public; invite users, apply presets, and get the new chat token.

Instructions

Create a new Talk conversation.

Args: room_type: 1 for a one-to-one conversation, 2 for a group conversation, 3 for a public one. Group conversations are invite-only; public ones can be joined via link. A one-to-one conversation with someone you already have one with returns the existing one. name: Display name for the conversation (ignored for one-to-one). invite: User ID to invite; required for one-to-one, optional for group. description: Optional description for group and public conversations. preset: Optional preset identifier from list_conversation_presets; its settings (permissions, lobby, read-only, ...) are applied to the new conversation. An explicit room_type still wins over the preset's.

Returns: JSON object with the created conversation details, including its token.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes
`invite`	No
`preset`	No
`room_type`	Yes
`description`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv0.9.0Oct 1, 2026

addedInput schema / properties / description

Added value: +{
+  "default": "",
+  "title": "Description",
+  "type": "string"
+}

addedInput schema / properties / preset

Added value: +{
+  "default": "",
+  "title": "Preset",
+  "type": "string"
+}

First observedv0.7.0Sep 21, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already establish the write/non-idempotent/non-destructive profile. Beyond that, the description adds genuinely useful behavior: the 1:1 dedup-and-return-existing rule, the fact that preset settings are applied and that an explicit room_type overrides the preset, and that the response carries a token. This is meaningful context that the annotations cannot express.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose leads and the Args/Returns structure is easy to scan; each clause carries information. It is somewhat long, but the length is justified by five undocumented parameters and non-obvious behaviors, so nothing is wasted.

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?

With an output schema present, the description need not detail return fields, yet it still notes the response includes the conversation token. Combined with full parameter documentation and the preset/room_type precedence rule, an agent has everything needed to call it correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full parameter burden and does it well: room_type is enumerated with meanings (1=one-to-one, 2=group, 3=public), invite is marked required for one-to-one and optional for group, name is noted as ignored for one-to-one, and description/preset scopes are stated.

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?

States a specific verb and resource ('Create a new Talk conversation'), which is unambiguous. It does not, however, differentiate itself from the many other create_* siblings (create_group, create_circle, create_collective, create_flow), so an agent gets a clear purpose but no routing help.

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?

Explains the conditional scenarios that matter: group conversations are invite-only, public ones are joinable via link, and a one-to-one with an existing partner returns the existing conversation. It gives clear context but never names an alternative tool or states explicit when-not-to-use conditions.

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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