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Chainsaw MCP Server

Chainsaw MCP Server

by MadameFabulous
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Chainsaw: SRUM analysis

chainsaw_analyse_srum

Analyse Windows SRUM database activity from SRUDB.dat and a SOFTWARE hive to extract per-app resource usage; optionally return stats only. Output is saved to a result handle for export.

Instructions

Analyse the System Resource Usage Monitor (SRUM) database.

Wraps chainsaw analyse srum. Output is stored under a result handle; use chainsaw_result_export for the complete text.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "srum_db": "<srum_db>",
      "software_hive": "<software_hive>"
    },
    "name": "chainsaw_analyse_srum"
  }
}

Input Schema

NameRequiredDescriptionDefault
srum_dbYesSRUDB.dat under an allowed evidence root.
stats_onlyNoOnly report table statistics, not the full extraction.
preview_bytesNoBytes of output to include inline.
software_hiveYesSOFTWARE registry hive under an allowed evidence root.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations declare readOnly=false, idempotent=false, destructive=false, but the description explains WHY this non-read-only analysis tool mutates state: output is stored under a result handle. It also clarifies inline output is a preview. That is genuine context beyond the structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences with no filler, and the core purpose is front-loaded before the wrapping detail and the output-routing note. Slightly more could be said about result-handle mechanics, but nothing is wasted.

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

Completeness4/5

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

No output schema exists, and the description compensates by explaining that output lands in a result handle and must be retrieved via chainsaw_result_export. Required inputs and their constraints are covered by the schema. Reasonably complete, though it omits any note on large-database runtime or evidence-root requirements.

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

Parameters3/5

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

Schema description coverage is 100%, so all four parameters (srum_db, software_hive, stats_only, preview_bytes) are already documented in the schema. The description adds nothing about parameter semantics; baseline 3 applies.

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 and resource ('Analyse the System Resource Usage Monitor (SRUM) database') and names the underlying command. An agent can distinguish it from other analyse_* siblings by resource, though the description never explicitly contrasts them.

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?

Provides a downstream routing hint ('use chainsaw_result_export for the complete text'), which is useful. However, it gives no guidance on when to choose SRUM analysis over the other analysis tools, and no prerequisites beyond what the schema enforces.

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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