Skip to main content
Glama
AhmadTariq1337

streamlabs-mcp

streamlabs_list_notifications

List Streamlabs Desktop in-app notifications, with optional filters for type and read state to track relevant alerts.

Instructions

List Streamlabs Desktop's in-app notifications, optionally filtered by type and read state.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional filter by notification type
onlyReadNoIf true, only return already-read notifications
onlyUnreadNoIf true, only return unread notifications
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. The verb 'List' implies a read-only operation, but the description does not explicitly state that it does not modify notification read state, nor does it address the interplay between onlyRead and onlyUnread (e.g., mutual exclusivity). This leaves some ambiguity about side effects.

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 a single, front-loaded sentence that states the primary action and optional filters without any redundant wording. It is efficient and easy to parse, earning a perfect score.

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

Completeness3/5

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

The tool is simple with three optional parameters and no output schema or annotations. The description covers the core purpose but leaves gaps: it does not explain default behavior when no filters are applied, the exact return format, or how conflicting filters (onlyRead and onlyUnread) are handled. For a list tool, these are not deal-breakers but would improve completeness.

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 coverage is 100%, so each parameter is already fully documented in the input schema. The description's mention of 'type and read state' adds no meaning beyond the schema's parameter descriptions. It simply rephrases them at a high level, so a baseline score of 3 is appropriate.

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 clearly specifies the verb 'List' and the resource 'Streamlabs Desktop's in-app notifications', making the tool's purpose explicit. It also mentions optional filters, which distinguishes it from sibling tools like mark_notification_read or push_notification.

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?

The description provides clear context by indicating it lists notifications and can be filtered. While it does not explicitly name alternative tools, the verb 'List' and the optional filters clearly communicate when to use this tool versus mutating or panel commands. The absence of explicit exclusions is acceptable given the simplicity of the operation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AhmadTariq1337/streamlabs-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server