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ThalesMMS

simple-dicom-mcp

by ThalesMMS

query_patients

Search for patients in a DICOM network by providing optional criteria such as patient ID or birth date, and customize which attributes are returned.

Instructions

Query patients matching the specified criteria from the DICOM node.

This tool performs a DICOM C-FIND operation at the PATIENT level to find patients matching the provided search criteria. All search parameters are optional and can be combined for more specific queries.

Args: patient_id: Patient ID to search for, e.g., "12345678" birth_date: Patient birth date in YYYYMMDD format, e.g., "19700101" attribute_preset: Controls which attributes to include in results: - "none": No attributes, use with additional_attributes (default) - "custom": Our custom attributes additional_attributes: List of specific DICOM attributes to include beyond the preset exclude_attributes: List of DICOM attributes to exclude from the results

Returns: Dictionary containing: - success: Boolean indicating if the query completed without failure - results: List of matched patient records - dicom_statuses: List of DICOM status entries - warnings: List of warning entries - error: Optional error dictionary

Example: { "success": true, "results": [ { "PatientID": "12345", "PatientBirthDate": "19700101", "PatientSex": "M" } ], "dicom_statuses": [{"code": "0x0000", "category": "success"}], "warnings": [], "error": null }

Notes: Returns success False if the query fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
patient_idNo
birth_dateNo
attribute_presetNonone
additional_attributesNo
exclude_attributesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description fully covers behavior: it performs a DICOM C-FIND, returns success/failure, and details the return structure. However, it does not explicitly state read-only or mention auth/rate limits.

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?

The description is well-structured with clear sections (Args, Returns, Example, Notes) and front-loaded purpose. It is efficient but slightly verbose with the example.

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 complexity and sibling tools at different DICOM levels, the description is complete: it explains level, parameters, return format, and error handling. The output schema is absent but the description compensates with a detailed example.

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 coverage is 0%, but the description provides detailed semantics for all 5 parameters, including examples and format hints (e.g., date format, attribute_preset options), adding substantial value beyond the schema.

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 it queries patients from a DICOM node using C-FIND at the PATIENT level, distinguishing it from sibling tools for studies, series, and instances.

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 explains that parameters are optional and combinable, but lacks explicit guidance on when to use this tool versus siblings like query_studies or query_series.

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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