{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_yh4q8vwcj7vj","handle":"tavimercy-dicom-mcp","url":"https://wellknown.network/agents/tavimercy-dicom-mcp","links":{"self":"https://wellknown.network/agents/tavimercy-dicom-mcp/record.json","html":"https://wellknown.network/agents/tavimercy-dicom-mcp","markdown":"https://wellknown.network/agents/tavimercy-dicom-mcp/record.md","api":"https://wellknown.network/api/v1/agents/tavimercy-dicom-mcp","status":"https://wellknown.network/api/v1/agents/tavimercy-dicom-mcp/status","claim":"https://wellknown.network/agents/tavimercy-dicom-mcp/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/tavimercy-dicom-mcp/claim.json","badge":"https://wellknown.network/agents/tavimercy-dicom-mcp/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/tavimercy-dicom-mcp/history","tools":"https://wellknown.network/api/v1/agents/tavimercy-dicom-mcp/tools"},"ard":{"identifier":"urn:air::server:tavimercy-dicom-mcp","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"tavimercy-dicom-mcp","summary":"基于 MCP (Model Context Protocol) 的 DICOM 医学影像文件分析工具","description":"# TaviMercy DICOM MCP\n\n[![PyPI version](https://badge.fury.io/py/tavimercy-dicom-mcp.svg)](https://pypi.org/project/tavimercy-dicom-mcp/)\n[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n\n基于 MCP (Model Context Protocol) 的 DICOM 医学影像文件分析工具。\n\n## 特性\n\n- 🔍 DICOM 文件扫描和解析\n- 📊 医学影像序列分析（主动脉、二尖瓣）\n- 📁 按患者和序列自动整理 DICOM 文件\n- 📈 导出测量数据为 CSV 格式\n- 🔌 完整的 MCP 协议支持\n- 🌐 与 Orthanc PACS 服务器集成\n\n## 安装\n\n### 使用 pip 安装\n\n```bash\npip install tavimercy-dicom-mcp\n```\n\n### 使用 uvx 直接运行（推荐）\n\n```bash\nuvx tavimercy-dicom-mcp\n```\n\n## MCP Server 配置\n\n在 MCP 客户端配置文件中添加以下配置：\n\n```json\n{\n  \"mcpServers\": {\n    \"tavimercy-dicom-mcp\": {\n      \"command\": \"uvx\",\n      \"args\": [\n        \"tavimercy-dicom-mcp==2.1.6\"\n      ],\n      \"env\": {\n        \"base_url\": \"https://your-server.com\",\n        \"name\": \"your_username\",\n        \"password\": \"your_password\",\n        \"tel\": \"your_phone\"\n      }\n    }\n  }\n}\n```\n\n**环境变量说明：**\n- `base_url`: 服务器基础URL（必需）\n- `name`: 用户名（可选，用于自动登录）\n- `password`: 密码（可选，用于自动登录）\n- `tel`: 手机号（可选，用于自动登录）\n\n## 工具说明\n\n### 1. scan-dicom-directory\n扫描指定目录下所有可读的 .dcm 文件，汇总患者数、序列数、文件数和总字节数，返回 JSON 文本。\n\n**参数：**\n- `directory_path` (string): 待扫描的本地目录路径，绝对路径，必须存在且可读\n\n### 2. parse-dicom-file\n解析单个 DICOM 文件，提取 PatientID、PatientName、SeriesInstanceUID、SeriesDescription 等元数据，返回结构化 JSON。\n\n**参数：**\n- `file_path` (string): 待解析的本地 DICOM 文件路径，需指向实际存在的 .dcm 文件\n\n### 3. analyze-dicom-directory\n扫描目录中的 DICOM 序列，按 series_type 选择分析流程并上传到预配置的远端分析服务，返回上传结果及访问 URL。\n\n**参数：**\n- `directory_path` (string): 包含待分析 DICOM 序列的本地目录路径，必须存在且具备读取权限\n- `series_type` (string): 分析流程类型，`1`=主动脉分析，`9`=二尖瓣分析\n\n### 4. separate-dicom-files\n按患者和序列拆分目录下的 DICOM 文件，生成新的子目录结构，并以 JSON 返回整理后的统计结果。\n\n**参数：**\n- `directory_path` (string): 待整理的顶层目录路径，执行过程中会在同级创建输出目录\n\n### 5. get-analysis-result\n根据 study_uid 查询分析结果，如果没有分析结果，需要进行 analyze-dicom-directory 工具上传分析，返回测量结果的 URL。\n\n**参数：**\n- `study_uid` (string): …","publisher":null,"homepage":"https://github.com/jiancongzhang/tavimercy-dicom-mcp","repository":"https://github.com/jiancongzhang/tavimercy-dicom-mcp","version":"2.1.6","license":"MIT","protocols":["mcp"],"tags":["dicom","mcp","medical-imaging","model-context-protocol","orthanc"],"pricing":null,"endpoints":[{"url":"pypi:tavimercy-dicom-mcp","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","license":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi"}},"derived":{"capabilities":[{"slug":"dev.filesystem","name":"Filesystem","confidence":0.802,"provenance":"derived"}],"categories":["dev"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"tavimercy-dicom-mcp","registry":"pypi","observedAt":"2026-11-04T02:26:19.093Z","publishedAt":"2025-12-11T08:44:45.889680Z","latestVersion":"2.1.6"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"tavimercy-dicom-mcp","url":"https://pypi.org/project/tavimercy-dicom-mcp/","firstSeenAt":"2026-09-10T13:20:59.376Z","fetchedAt":"2026-11-04T02:24:27.720Z","normalizedAt":"2026-11-04T02:24:27.720Z"}]},"firstSeenAt":"2026-09-10T13:20:59.376Z","updatedAt":"2026-11-04T02:26:19.093Z"}