tenable-patch-management-logs-mcp

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summarize_errors

Read-onlyIdempotent

Identifies and groups warnings and errors from Tenable Patch Management logs into ranked issues with known fixes, root causes, and remediation steps. Start here to understand what went wrong.

Instructions

Group every warning and error into distinct issues, ranked, with known fixes.

The best first call for "what is wrong?". Repeats are collapsed into signatures (IDs, GUIDs, IPs, numbers and paths normalised); the same event written to several logs is counted once. Each issue has counts, first/last seen, devices, decoded error codes, root causes from stack traces, the latest example with file and line, and - when recognised - a known-issue explanation and remediation. INFO lines that carry stack traces are raised to ERROR (flagged). Known platform noise is counted under noise instead of cluttering issues.

Args: since: Window start: ISO time (2026-09-17T08:00) or relative (90m, 24h, 7d, 2w) counted back from the newest log entry. Default 7d. until: Window end (same formats). Default: newest entry. source: Source name; omit for all sources. device: Only this device. role: "server", "client" or "setup". files: Log names or globs, e.g. ["VulnerabilityManagement.log"]. min_severity: WARN (default), ERROR or FATAL. include_noise: Include known platform noise in issues. top: Issues to return (1-100).

Returns: totals, ranked issues, noise, top components/logs and coverage.

Input Schema

TableJSON Schema

Name	Required	Default
`top`	No
`role`	No
`files`	No
`since`	No	7d
`until`	No
`device`	No
`source`	No
`min_severity`	No	WARN
`include_noise`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 23, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds rich behavioral detail beyond that: repeat collapsing via normalized signatures, cross-log duplicate counting, INFO lines with stack traces elevated to ERROR, known platform noise separated into `noise`, and per-issue metadata like counts, first/last seen, devices, root causes, and fixes.

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?

The description is front-loaded with the core purpose, then provides dense but scannable behavioral details and an Args/Returns structure. Every sentence earns its place; the length is justified by the complexity of a 9-parameter diagnostic tool.

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

Completeness5/5

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

Given the complexity and the 0% schema description coverage, the description is complete: it explains filtering, deduplication, severity elevation, noise handling, known-fix metadata, and return sections. An output schema exists to handle detailed return structure, so no essential guidance is missing.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden for all 9 parameters. The Args section documents every parameter with formats, defaults, allowed values, examples, and semantics, e.g. `since` supports ISO or relative times, `role` accepts server/client/setup, `files` accepts globs, and `top` is bounded to 1-100.

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

Purpose5/5

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

The description uses a specific verb and resource: 'Group every warning and error into distinct issues, ranked, with known fixes.' It also positions itself as 'The best first call for "what is wrong?"', which clearly distinguishes it from sibling tools like search_logs, diagnose, and detect_log_anomalies.

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

Usage Guidelines4/5

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

The description gives clear situational advice: use this as the first call when diagnosing what is wrong. It does not, however, explicitly name siblings as alternatives or state cases where another tool such as search_logs or diagnose should be preferred instead, so it stops just short of full exclusion guidance.

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

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