Skip to main content
Glama
awesomemotive

pushengage-mcp

Create a subscriber attribute

pushengage_create_attribute

Create a custom subscriber attribute to capture extra data, such as plan type or signup source, then use it to build audience segments.

Instructions

Creates a new subscriber attribute on the current site. Required: name (human-readable label, e.g. "Customer Plan") and key (machine identifier, e.g. "plan"). The key must start with a letter and contain only letters, numbers, hyphens, and underscores. The created key becomes a usable value for audience-group rules with field="attributes" (the rule's key property). PushEngage caps each site at 50 attributes; the API returns 422 if the limit is exceeded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesThe machine identifier used in the JavaScript SDK and in audience-group rules. Must start with a letter and only contain letters, numbers, hyphens, and underscores. Max 64 chars. e.g. "plan", "signup_source", "lifetime-value". This is the same key you pass as `key` on an audience-group rule with field="attributes".
nameYesHuman-readable attribute name shown in the dashboard. 1–128 chars. e.g. "Customer Plan", "Sign-up Source".
site_idNoOverride the currently selected site.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
keyNo
nameNo
statusNo
view_urlNo
use_with_audience_group_ruleNo
Behavior4/5

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

Beyond the annotations, the description discloses a critical behavioral trait: PushEngage caps each site at 50 attributes and the API returns 422 when exceeded. It also explains the relationship between the created key and audience-group rules, adding context that annotations do not provide. It doesn't mention auth requirements or response shape, but the output schema covers the response.

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 four sentences long, front-loaded with the main purpose, and every sentence adds value: required fields, key format, audience-rule integration, and limit behavior. No unnecessary words or repetition of schema data.

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?

Given a fully documented schema, annotations, and an output schema, the description covers the essential behavioral constraints (key format, limit, audience-rule usage). It doesn't describe the success response, but that is already provided by the output schema. The only minor gap is lack of explicit guidance on when not to use this tool, but overall it is contextually complete.

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% with detailed descriptions and examples for all three parameters. The description adds some contextual meaning (e.g., the audience-rule usage) but largely restates what the schema already provides. The 50-attribute limit is not a parameter-specific detail, so the added value on parameter semantics is marginal; baseline 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 opens with a specific verb+resource: 'Creates a new subscriber attribute on the current site.' It distinguishes itself from siblings like create_segment and create_audience_group by explicitly naming the resource (attribute) and providing meaningful details (required name/key, examples).

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?

Clear context is provided: it explains that the created key becomes usable in audience-group rules, and notes the 50-attribute cap. However, it does not explicitly state when to use this tool over alternatives or when not to use it, so it falls short of the 'explicit exclusions/alternatives' bar.

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/awesomemotive/pushengage-mcp'

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