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Strac MCP DLP

Strac MCP DLP

Official
by strac-io
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Detect sensitive data in a file

detect_file

Detect PII, PHI, PCI, and secrets in local files—including images, PDFs, and scans—using OCR. Returns found data element types without modifying the file.

Instructions

Detect PII, PHI, PCI and secrets in a local file — image, PDF, scan or text. Strac runs OCR on images and scanned documents. Returns the data element types found, without modifying the file.

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": {
      "path": "<path>"
    },
    "name": "detect_file"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes
include_matched_textNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently states that Strac runs OCR on images/scanned documents, returns the found data element types, and does not modify the file. It does not cover edge cases like no matches or file access requirements, but the core behavior is well disclosed.

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 three sentences with no fluff. It front-loads the core purpose, then gives OCR context, then states the output and non-mutating behavior. Every sentence earns its place and the length is appropriate for the tool's complexity.

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?

Given the output schema exists, the description does not need to explain return structures. It covers the key operational aspects: supported file types, OCR behavior, data categories, and non-modification. The main gap is that it leaves the meaning of include_matched_text unexplainede and does not mention any file-size or access prerequisites, but overall it is complete enough for a detection tool with this schema.

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 description coverage is 0%, so the description should compensate for parameter meaning. It does not mention 'path' or 'include_matched_text' at all; the optional matched-text behavior is entirely absent. The schema's property names are self-descriptive, but the description adds no value beyond the schema and fails to clarify what include_matched_text affects in the results.

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?

The description clearly states a specific action (detect), a resource (local file), and target data categories (PII, PHI, PCI, secrets). It also distinguishes file types and notes that OCR is applied to images/scans. However, it does not explicitly differentiate this tool from the sibling detect_sensitive_data, so the sibling advantages are not directly addressed.

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 implies when to use this tool: when you have a local file (image, PDF, scan or text) and need detection without modification. It also implies OCR handling for images/scans. But it does not explicitly state when not to use it or name alternatives such as detect_sensitive_data, and no usage exclusions are provided.

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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