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Forensics Utils MCP Server

Forensics Utils MCP Server

by jus1-c
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

firefox_parse_history_tool

Extract and filter Firefox browsing history from a profile directory for forensic analysis. Specify profile path, optional URL/title filters, and limit results.

Instructions

Parse Firefox browsing history records from a browser profile. Typical profile path: "C:\Users<user>\AppData\Roaming\Mozilla\Firefox\Profiles<rand>.default-release".

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": {
      "profile_path": "<profile_path>"
    },
    "name": "firefox_parse_history_tool"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlNoOptional exact URL filter
limitNoMaximum number of history records to return
titleNoOptional exact page title filter
profile_pathYesAbsolute path to the Firefox profile directory

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are present, so the description must carry the full burden. It says 'parse' but does not explicitly state that this is a read-only operation or disclose any side effects, permissions, or potential failure modes. The only added context is the profile path, which is minimal.

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 two sentences: the first states the purpose, the second gives a concrete example path. It is front-loaded, concise, and every sentence provides value with no fluff.

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?

Given that an output schema exists and all parameters are documented, the description is adequate for basic invocation. However, it lacks behavioral transparency (no read-only disclosure) and usage guidance (no when-to-use vs alternatives), making it minimally complete rather than comprehensive.

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 coverage is 100% with each parameter (profile_path, url, limit, title) having a description, so the schema already handles parameter semantics. The description adds the example profile path format, but that's also evident from the schema. Baseline of 3 is appropriate.

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 clearly states 'Parse Firefox browsing history records from a browser profile' using a specific verb and resource, which distinguishes it from sibling tools like firefox_parse_bookmarks_tool and chromium_parse_history_tool. The scope is precise and actionable.

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?

The description provides a typical profile path, which implies when to use (e.g., when analyzing Firefox history), but does not explicitly mention when not to use or alternatives. Usage context is implied rather than clearly stated.

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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