pipefy Observability
Monitor AI agent and automation execution, usage stats, credit consumption, and export job history. 11 MCP tools.
Identifiers reference
Full cross-tool map: docs/mcp/tools/identifiers.md#observability.
| Concept | What tools expect | How to obtain |
|---|---|---|
| Pipe for AI agent logs | repo_uuid — the pipe UUID |
get_pipe with numeric pipe_id; use pipe.uuid. |
| Automation for logs | automation_id — numeric |
get_automations pipe_id=... |
| Org for usage stats | organization_uuid — UUID or numeric org id |
get_organization returns the uuid; a numeric id also works (resolved server-side). Execution-metrics / export take numeric organization_id. |
Tools
| Tool (MCP) | CLI | Read-only | Purpose |
|---|---|---|---|
get_ai_agent_logs |
pipefy agent logs list |
Yes | Execution history for a specific AI agent. |
get_ai_agent_log_details |
pipefy agent logs get |
Yes | Single execution detail for an AI agent log entry. |
get_automation_logs |
pipefy automation logs --automation |
Yes | Execution history for an automation (by automation ID). |
get_automation_logs_by_repo |
pipefy automation logs --repo |
Yes | Automation logs filtered by pipe. |
get_agents_usage |
pipefy usage agents |
Yes | Org-level AI agent execution count and trends. |
get_automations_usage |
pipefy usage automations |
Yes | Org-level automation execution stats. |
get_automation_execution_metrics |
pipefy usage execution-metrics |
Yes | Per-automation execution metrics (totalRuns, success/failure rate, avg duration, lastRun) over a rolling window; partial success returns partial_errors for denied ids. |
get_ai_credit_usage |
pipefy usage credits |
Yes | AI credit consumption and remaining balance. |
export_automation_jobs |
pipefy export automation-jobs |
Yes | Trigger async export of automation job history. |
get_automation_jobs_export |
pipefy automation export status |
Yes | Poll export job status (after export_automation_jobs). |
get_automation_jobs_export_csv |
pipefy export automation-jobs-csv |
Yes | Download finished automation-jobs export as CSV text. |
Steps — diagnose a failing AI agent
Get the pipe UUID (not the numeric pipe ID):
MCP:
get_pipe pipe_id=67890Capture
pipe.uuidfrom the response.Fetch recent agent logs:
MCP:
get_ai_agent_logs repo_uuid=<UUID> page=1Identify the failed execution — look for
status: failedentries.Check credit usage if the agent stopped unexpectedly:
MCP:
get_ai_credit_usage organization_id=123Fix and re-enable — update the agent config (see
skills/ai-agents/) and toggle status:MCP:
toggle_ai_agent_status agent_id=456
Steps — export automation history as CSV
Trigger the export:
MCP:
export_automation_jobs organization_id=123 period="current_month"Poll for completion:
MCP:
get_automation_jobs_export export_id=<EXPORT_ID>Repeat until
statusisfinishedorfailed.Fetch CSV text (when finished):
MCP:
get_automation_jobs_export_csv export_id=<EXPORT_ID>
Success criteria
- Agent logs show execution timestamps and statuses.
- Credit usage shows remaining balance; no unexpected drops.
- CSV export downloads successfully and contains expected automation history.
Failure modes
get_ai_agent_logsreturns empty: use the pipe UUID (e.g.,abc123-...), not the numeric pipe ID. Get UUID fromget_pipe.get_automation_jobs_exportstays inprocessing: large exports take time. Wait at least 60 seconds between polls. If stillprocessingafter several minutes, retry the export trigger.- Credit usage shows 0 remaining: alert the user — AI features will stop working until credits are replenished. Escalate to the Pipefy admin.
See also
skills/ai-agents/— create and configure AI agents.skills/automations/— create and debug automation rules.