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Glama

CustomerDashboard

Add a customer login

add_customer_user

Create a login for one of your customers so they can sign in to the published dashboard and see their own data. If you do not supply a password a strong one is generated and returned once. Subject to your plan's users-per-customer limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesThe person's email address. Must be unique on this dashboard.
passwordNoLeave empty to have a strong password generated.
dashboardIdYesDashboard id.
customerRecordIdYesThe customer's id from list_customers.

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

The description adds useful behavioral detail beyond the annotations: password generation behavior, one-time return of the generated password, and the plan's users-per-customer limit. It does not cover every edge case, such as duplicate email or idempotency, but it meaningfully informs the agent.

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, front-loaded with the core action, and every sentence earns its place. It states purpose, a key behavioral nuance, and a constraint without any filler.

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

Completeness5/5

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

For a write operation with no output schema, the description is remarkably complete: it explains the purpose, the needed input context, password behavior, one-time return, and plan limitation together with fully described parameters. An agent has enough information to invoke this tool correctly.

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 all four parameters are already documented. The description's note about password generation largely repeats the schema's 'Leave empty to have a strong password generated' text, adding no new per-parameter meaning.

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 uses a specific verb-resource pair ('Create a login for one of your customers') and explains the benefit: the customer can sign in to the published dashboard and see their own data. This clearly distinguishes it from add_customer and delete_customer_user.

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 clearly establishes when to use the tool: when a customer needs login access to a published dashboard. It does not explicitly name alternatives or state when not to use it, but the context is strong enough that an agent can select it correctly.

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

A3.9/5.0
Disambiguation4/5

Most tools target a distinct resource+action pair, and descriptions explicitly cross-reference related tools (e.g. update_dashboard points to set_dashboard_theme and publish_dashboard). A few pairs remain close enough to cause hesitation—set_widget_layout vs update_widget's position parameter, and get_started vs get_platform_overview—but their descriptions do separate them.

Naming Consistency4/5

Tool names consistently follow verb_noun snake_case with clear resource nouns like customer, dashboard, widget, and data_source. Minor deviations exist between add_* and create_* for creation operations, and set_* versus update_* for mutations, but the overall pattern is still predictable.

Tool Count2/5

With 42 tools, the surface is much larger than the 16-25 range that already feels heavy, and several onboarding/catalog helpers (get_started, get_platform_overview, list_plans_and_limits, list_supported_data_connectors, list_widget_types) add to the count. Each tool has a distinct job, but the set would benefit from consolidation or splitting into focused sub-servers.

Completeness4/5

Core lifecycle coverage is strong: dashboards, views, widgets, data sources, customers, and publishing all have create/read/update/delete where relevant, plus test/preview/validation tools. Obvious gaps are customer-user management beyond create/delete (no password reset/update) and no direct way to move a widget between views, but agents can work around these.

Resources