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nifi_provenance_query

Read-onlyIdempotent

Search Apache NiFi provenance events to trace what happened to data. Filter by filename, event type, component, or FlowFile UUID to investigate past flow activity.

Instructions

Search provenance events to trace what happened to data.

Backed by POST /provenance, polled to completion. Dates use NiFi's MM/dd/yyyy HH:mm:ss format. This reads history only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNo
filenameNo
event_typeNo
start_dateNo
max_resultsNo
component_idNo
flowfile_uuidNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, and non-destructive behavior, so the bar is lower. The description adds genuinely useful operational context beyond that: it is backed by POST /provenance, polled to completion (implying latency), and constrained to history reads.

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?

Extremely tight: three short sentences, purpose front-loaded first, with operational notes after. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be described, and the date format and polling behavior are covered. But with 7 undocumented parameters and no sibling disambiguation, the definition is only minimally complete for a query tool of this complexity.

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

Parameters2/5

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

Schema coverage is 0% across 7 parameters, so the description carries the full burden. It documents only the date format and leaves filename, event_type, component_id, flowfile_uuid, max_results, and the start/end pairing unexplained, so an agent cannot infer their semantics from the description alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (search), resource (provenance events), and goal (trace what happened to data), which is far more than a restatement. However, it does not differentiate from close siblings such as nifi_get_lineage or nifi_get_provenance_event, whose purposes overlap with historical data tracing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"This reads history only" implies a read-only historical context, but there is no explicit statement of when to use this versus nifi_get_lineage or nifi_get_provenance_event. Usage is implied rather than directed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.