nc-mcp-server

search_mentions

Read-onlyIdempotent

Find who can be mentioned in a conversation by searching partial names or IDs. Returns the exact mention text (e.g., @"john.doe") for writing messages.

Instructions

Find who can be mentioned in a conversation, for writing a message that mentions them.

Args: token: The conversation token. search: Part of a name or ID; an empty string lists the first matches. limit: Maximum results (1-50, default 20). Needs a conversation you can write in.

Returns: JSON list of matches with id, label (display name), source (users, groups, guests, calls for everyone in the room, ...) and "mention", the text to put in the message, e.g. @"john.doe".

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "token": "<token>",
      "search": "<search>"
    },
    "name": "search_mentions"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`token`	Yes
`search`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.9.0Oct 1, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so safety is covered. The description adds real behavioral context beyond that: the write-permission prerequisite and the shape of the response (id, label, source, and the ready-to-use 'mention' text). It does not mention rate limits or pagination, but it is genuinely additive.

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?

Front-loads the purpose, then a structured Args/Returns block where every line adds semantics. The permission note is slightly awkwardly tucked into the limit line, but overall it is tight and well-organized for its information density.

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?

Even though an output schema exists, the description still explains the return contents usefully. Combined with full parameter coverage and the write-permission prerequisite, 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 coverage is 0%, so the description carries the full burden, and it fully compensates. It explains token, that search matches a name/ID with an empty string listing first matches, and that limit caps results at 1-50 with a default of 20 - semantics well beyond the bare schema.

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 ('Find who can be mentioned in a conversation') plus the motivating use case (writing a mentioning message). This is clearly distinct from list-style siblings like get_participants, though it does not explicitly name an alternative to route against. Strong but not maximally differentiated.

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?

Gives clear context for when to use it ('for writing a message that mentions them') and a prerequisite ('Needs a conversation you can write in'). It stops short of naming excluded cases or a competing tool, so it is clear context without explicit alternatives.

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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