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CustomerDashboard

Update a data source

update_data_source
Idempotent

Rename a data source or replace its connection settings. The config you pass replaces the stored one entirely, so include every setting, not just the changed ones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
configNoConnection 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.
dataSourceIdYesData source id.

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations show destructiveHint=false, idempotentHint=true, and readOnlyHint=false, so the mutation behavior is already signaled. The description adds valuable transparency by warning that the config replaces the stored one entirely—a potentially destructive aspect for an agent to know. It also benefits from the schema note that credentials are encrypted and never returned by read tools, which covers a behavioral concern beyond basic annotations.

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?

Two sentences, front-loaded with the main actions, then the critical replacement warning. No filler or repetition of what the schema already states.

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 mutation tool with no output schema, the description covers the key behavioral context: what it changes, how config replacement works, and the security note in the schema. It doesn't mention idempotency or prerequisites, but the annotations already cover idempotency, and no output schema means return behavior isn't expected. Minor gap: it doesn't state that name is optional or that only dataSourceId is required, but the schema covers that.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 67%, with only dataSourceId and config having descriptions. The description explains the config parameter's replacement semantics and the name parameter's purpose implicitly, while the schema adds a concrete example for config and a useful security note. The only gap is that 'name' is not explicitly described in the description, but it is straightforward from context.

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 states two distinct operations: rename a data source or replace its connection settings. It names the resource (data source) and uses specific verbs (rename, replace) that distinguish it from sibling tools like test_data_source_connection or get_data_source.

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 on when to use the tool: when renaming or updating connection settings. It also includes a crucial usage warning that the config replaces the stored one entirely, which guides correct invocation. It doesn't explicitly name alternatives, but the sibling list makes the context reasonably clear.

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