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Query channels

stream_query_channels
Read-only

List/filter channels by a Stream query filter. e.g. filter {"type":"messaging"} or {"members":{"$in":["user-1"]}}. Returns channels with recent state. POST /api/v2/chat/channels.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoDefault [{"field":"last_message_at","direction":-1}].
limitNoMax channels (<=30). Default 30.
filterNoStream filter_conditions object, e.g. {"type":"messaging"} or {"members":{"$in":["u1"]}}. Default {} (all channels the app can see).
offsetNoPagination offset.
message_limitNoRecent messages per channel to include. Default 25.

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

The readOnlyHint annotation already establishes that this is a safe read operation. The description adds useful behavioral context beyond that by noting it returns channels with recent state and by giving the exact endpoint, POST /api/v2/chat/channels. It stops short of describing pagination or response shape, but the annotation lowers the bar and this is meaningful extra 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?

The description is compact and front-loaded with the core purpose, followed by a useful example and a return-value note. Every sentence earns its place, and the endpoint line is a practical bonus without padding.

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 read-only list tool with well-described optional parameters, the description covers the essential purpose, filter semantics, return gist, and endpoint. There is no output schema, so a bit more detail on the returned channel representation could help, but the schema and examples make it adequate for a competent agent.

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 description coverage is 100%, so the schema already documents all five parameters and their defaults; the baseline of 3 applies. The description's filter examples add clarity but duplicate the filter parameter's own schema description rather than introducing new semantic information.

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-resource pair, 'List/filter channels,' and identifies the distinguishing mechanism (a Stream query filter) with two concrete examples. This makes the tool immediately distinguishable from siblings like get_channel (single-channel retrieval) and query_users/query_threads.

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 'List/filter channels by a Stream query filter,' but the description never states when to prefer this over alternatives such as stream_get_channel or stream_query_threads. No exclusions or when-not guidance is provided, though the intended use case is reasonably inferable.

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.