Trodo MCP uses five scopes. Four are on by default; the PII scope is opt-in.Documentation Index
Fetch the complete documentation index at: https://docs.trodo.ai/docs/llms.txt
Use this file to discover all available pages before exploring further.
The five scopes
| Scope | Default | Description |
|---|---|---|
mcp:events | ✓ ON | Query event counts, funnels, retention, sessions, breakdowns, anomalies, cohort comparisons, paths. No personally-identifying data. |
mcp:agent_runs | ✓ ON | List + inspect AI-agent runs, their span trees, error rates, costs, feedback. |
mcp:cluster | ✓ ON | Browse use-case + issue clusters of agent conversations. |
mcp:evals | ✓ ON | List evaluators and results, manage the human eval queue, submit grades, and create new evaluators. |
mcp:user:read_pii | ✗ OFF | Look up individual users by identifier or fuzzy match. Returns emails, wallet addresses, country, device. Off by default. |
Tool → scope mapping
mcp:events
run_insights_query, run_funnel_query, run_retention_query, get_segment_comparison, get_utm_attribution_analysis, get_top_users, get_session_analysis, get_property_distribution, compare_periods, get_event_correlation, get_anomaly_detection, get_cohort_compare, get_path_analysis, get_rage_click_analysis, get_scroll_depth_analysis, get_exit_intent_analysis, get_form_abandonment_analysis, get_js_error_analysis, get_error_impact_on_funnel, get_page_performance_analysis, get_network_error_analysis, list_event_names, list_event_properties, list_property_values, create_report
mcp:agent_runs
list_agent_runs, get_agent_run, search_agent_runs, get_failed_user_attempts, get_run_metrics, get_token_cost_breakdown, get_tool_call_analysis, get_top_failure_modes, get_agent_feedback_summary, list_agent_names, list_agent_run_dimensions
mcp:cluster
list_use_case_clusters, get_cluster_runs, get_cluster_summary, list_issues, get_issue_details, get_issue_timeline, get_top_failing_tools, get_ux_rage_hotspots, report_heal_branch
mcp:evals
list_evaluators, get_evaluator, get_eval_results, get_eval_results_for_run, get_eval_results_for_span, list_pending_human_evals, submit_human_eval_grade, create_evaluator
mcp:user:read_pii
get_user_profile, get_user_journey, find_users, find_users_by_wallet, list_groups, get_group_profile
Combined scopes
get_user_agent_runs— requires bothmcp:agent_runsANDmcp:user:read_pii(it joins agent runs with a user identifier).get_users_with_eval_score— requires bothmcp:evalsANDmcp:user:read_pii(returns user identities ranked by eval score).
Choosing scopes
For most analytics use cases, the three default scopes are enough. Claude can answer questions about engagement, conversion, agent performance, and cluster trends without ever seeing user PII. Enablemcp:user:read_pii if you specifically want Claude to investigate individual users (e.g. “what did user [email protected] ask my agents this week”). The consent screen calls this out separately and the API key UI requires checking the box explicitly.
mcp:evals is on by default because viewing eval results and managing the human eval queue are core analytics workflows with no PII exposure (evals are keyed by run/span IDs, not user identities).