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Query channel members

stream_query_members
Read-only

List/filter the members of one channel. Requires the channel type + id. Optional member filter, e.g. {"name":{"$autocomplete":"jo"}}. GET /api/v2/chat/members.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesChannel id.
sortNoSort spec, e.g. [{"field":"created_at","direction":1}].
typeYesChannel type, e.g. "messaging".
limitNoMax members (<=100). Default 100.
filterNoMember filter_conditions, e.g. {"user_id":{"$in":["u1","u2"]}}. Default {}.
offsetNoPagination offset.

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

The readOnlyHint annotation already establishes safety, and the description adds useful behavioral context: it is a GET request, scoped to one channel, with an optional filter. It does not describe pagination or return structure, but for a read-only list tool this is sufficient without an 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?

Three compact sentences deliver the core action, required parameters, an example, and the endpoint with no filler. The main purpose is front-loaded, and every sentence earns its place.

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?

The input schema documents all six parameters, annotations cover the read-only safety profile, and the description adds the endpoint and a filter example. For a straightforward channel-member listing tool, the missing return-shape details are a minor gap rather than a blocking omission.

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 coverage is 100%, so the baseline is 3. The description adds value beyond the schema by showing a realistic filter example ({"name":{"$autocomplete":"jo"}}) and emphasizing that type and id are required, which helps an agent form valid calls quickly.

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 'List/filter the members of one channel,' giving a specific verb, resource, and scope that distinguishes it from sibling tools like stream_query_channels or stream_query_users. The 'one channel' qualifier makes the tool's targeting unambiguous.

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 clearly states the required inputs ('channel type + id'), notes the optional member filter, and gives the HTTP endpoint. It does not explicitly name sibling alternatives or exclusion conditions, but the context makes it evident when this tool should be selected.

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

A4/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: app info, channel state, messages, reactions, replies, unread counts, and various query types. Even similar tools like get_channel vs query_channels are clearly separated by single-item vs list operations.

Naming Consistency5/5

All tools follow the consistent pattern stream_<verb>_<resource> (e.g., stream_get_message, stream_query_channels, stream_send_message). Verb usage is coherent across the set.

Tool Count5/5

With 13 tools, the set is well-scoped for a chat API server, covering core read, query, search, and write operations without excessive fragmentation.

Completeness4/5

Core chat workflows are covered: app info, channel access, messaging, reactions, threads, unread counts, and user/channel queries. Missing mutations like channel/message update or delete are notable but not severe, as the get-or-create channel behavior and send actions cover primary use cases.