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Scored across 33 tools
Each tool targets a specific GCP resource and action (e.g., gcloud_auth_login vs gcloud_auth_print_access_token), and even similar-looking tools like gcloud_storage_buckets_list vs gcloud_storage_ls are clearly distinct (buckets vs objects). The catch-all gcloud_execute is explicitly for commands not covered, so it doesn't cause ambiguity.
All tools follow a strict pattern: 'gcloud_<service>_<resource>_<verb>' (e.g., gcloud_container_clusters_list, gcloud_bq_query). The naming is uniform with consistent snake_case and predictable hierarchy, making it easy for an agent to infer function from name.
With 33 tools, the set is fairly large for an MCP server. While each tool targets a distinct GCP operation, the scope feels broad—covering many services but not deeply. The count exceeds the typical well-scoped range (3-15), but the consistent naming and organization mitigate confusion. It's borderline too heavy.
The tool set provides good coverage for listing and describing resources across several services, but many fundamental lifecycle operations are missing: no create/delete for Cloud Storage buckets, no update/delete for BigQuery, no create for Dataflow or Compute instances. The presence of gcloud_execute can fill gaps but at the cost of consistency and type safety.