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Glama

CustomerDashboard

Add a data source

add_data_source

Connect a new database or spreadsheet to your workspace. Test the settings with test_data_source_connection first: this tool saves them whether or not they work. Subject to your plan's data source limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesA name for this connection, shown in the dashboard editor.
typeYesConnector type. Call list_supported_data_connectors for the settings each one expects.
configYesConnection settings for this connector type, for example { host, port, database, username, password, ssl } for postgres. Credentials are stored encrypted at rest and are never returned by read tools.

Schema Changelog

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

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description reveals critical behavior beyond the annotations: credentials are saved regardless of whether the connection test succeeds, and the operation is subject to plan limits. This materially changes how an agent should invoke the tool, so the disclosure is valuable.

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 short sentences, each earning its place: the purpose, the critical testing caveat, and the plan-limit constraint. No filler or redundancy.

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 create-style tool with a nested config object and no output schema, the description covers the essential operational context: test first, settings persist even on failure, and plan limits apply. The schema handles parameter details, so nothing critical is missing.

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 input schema already documents name, type, and config. The description adds no parameter-specific semantics beyond the high-level mention of databases and spreadsheets, which is consistent with the baseline for full schema coverage.

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 states a specific action and resource: connect a new database or spreadsheet to your workspace. This clearly distinguishes it from sibling tools like get_data_source, update_data_source, and delete_data_source by signaling that it creates a new connection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly names the alternative test_data_source_connection and instructs the agent to use it first, warning that add_data_source saves settings even if they don't work. It also notes the plan data source limit, giving a clear condition on when adding may fail.

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