nc-mcp-server

get_reactions

Read-onlyIdempotent

List who reacted to a specific message and with which emoji. Filter results by a particular reaction if needed.

Instructions

List who reacted to a message, and with what.

Args: token: The conversation token. message_id: The message ID. reaction: Only this reaction, e.g. "👍" (default: all).

Returns: JSON object mapping each reaction to the display names of who used it.

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>",
      "message_id": "<message_id>"
    },
    "name": "get_reactions"
  }
}

Input Schema

Name	Required	Description	Default
`token`	Yes
`reaction`	No
`message_id`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.9.0Oct 1, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is fully covered. The description adds that the return is a JSON map of reaction to display names and gives an example reaction, but does not disclose pagination, result limits, or auth requirements beyond the token. Moderate added value against an already-strong annotation set.

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-loaded purpose sentence followed by clearly sectioned Args and Returns blocks. Sized appropriately with no filler. The Args/Returns blocks partly duplicate the input and output schemas, a minor redundancy.

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

Completeness4/5

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

For a simple read tool with annotations covering safety and an output schema covering return values, the description supplies the missing parameter semantics and a return summary. It is complete enough to invoke correctly, with only pagination/scope edge cases left unaddressed.

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

Parameters4/5

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 burden. It documents all three parameters and adds genuine meaning for 'reaction' via an example emoji and the default-all behavior. The token and message_id entries are thinner, largely restating names, keeping it from a 5.

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 states a specific verb and resource: 'List who reacted to a message, and with what.' An agent can immediately tell this is a read operation over a message's reactions. It does not explicitly differentiate itself from siblings like add_reaction or remove_reaction, so it earns a 4 rather than a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the purpose and the read-only nature of the operation, but there is no explicit guidance about when to reach for this tool versus add_reaction/remove_reaction or other message-context tools. The 'default: all' note for the reaction filter is the only usage-adjacent hint, leaving real routing to inference.

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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