list_spacesList the Spaces (collaboration workspaces) the API token owner is a member of. A Space holds campaigns; most other tools are Space-scoped. Use a returned id with set_active_space to switch the active Space for subsequent calls, or pass it as space_id on individual calls.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds meaningful context by stating that only Spaces the API token owner is a member of are returned. It also explains the relationship between Spaces and campaigns, which aids understanding of the tool's role in the wider workflow.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long with no wasted words. Each sentence earns its place: the first states the core function, the second provides domain context, and the third gives practical usage instructions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description provides enough context for a zero-parameter list tool. It explains what Spaces are, how they relate to other tools, and how the returned id should be used, making the tool fully understandable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds no parameter-specific information because none exist, but it does explain how to use the output id, which is indirectly related to parameters in subsequent calls.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool lists Spaces (collaboration workspaces) the API token owner is a member of, using a specific verb and resource. It also distinguishes the tool by explaining what a Space is and that most other tools are Space-scoped, which clarifies its unique role among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: to discover available Spaces for the token owner, then use the returned id with set_active_space or as space_id. It does not explicitly name an alternative tool, but the guidance is sufficient for a list operation with no direct sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools follow a clear resource+action pattern (get_ad, update_ad, delete_ad), so entity-level tools are easy to distinguish. The main ambiguity is among reporting/status tools like get_conversion_status, get_conversion_health, get_conversion_report, and account_summary vs. get_performance_stats, which could tempt misselection without reading descriptions.
Naming is highly consistent: nearly every resource has create_/get_/update_/delete_/list_ variants, with predictable special verbs like set_, trigger_, preview_, and upload_. Minor exceptions like account_summary or get_angle_readout still follow the same readable verb-driven style.
83 tools is an extreme surface for an MCP server, even one covering ad management. Most entities have full CRUD plus many custom readouts and report variants, which creates context bloat and makes tool selection unnecessarily expensive for the agent.
The platform covers the full campaign lifecycle: campaigns, ad groups, ads, keywords, assets, business/creative planes, conversion actions, sync, budget, and targeting are all represented. Minor gaps exist—conversion sources have create/list but no get/update/delete, and there is no explicit way to update or remove a conversion source—but these can be worked around.