MCP Server Mermaid
MCP Mermaid

Динамическая генерация mermaid диаграмм и графиков с помощью AI MCP. Вы также можете использовать:
mcp-server-chart для создания диаграмм, графиков и карт.
Infographic для создания инфографики, такой как
Timeline,Comparison,List,Processи т.д.🖼️ figure.ling.pub/gallery для просмотра и обмена сгенерированными ИИ диаграммами и рисунками, созданными с помощью mcp-mermaid и других инструментов.
✨ Возможности
Полная поддержка всех функций и синтаксиса
Mermaid.Поддержка конфигурации
backgroundColorиtheme, что позволяет крупным языковым моделям выводить богатые стилистические настройки.Поддержка экспорта в форматы
base64,svg,mermaid,file, а также удобные для удаленного использования форматыsvg_urlиpng_url, с проверкойMermaidдля облегчения многоэтапного вывода правильного синтаксиса и графики моделью. ИспользуйтеoutputType: "file"для автоматического сохранения PNG-диаграмм на диск для AI-агентов или режимы URL для обмена диаграммами через публичные ссылки mermaid.ink.
Related MCP server: Mermaid-MCP
🤖 Использование
Для использования с Desktop APP, такими как Claude, VSCode, Cline, Cherry Studio и другими, добавьте конфигурацию MCP-сервера ниже. В системе Mac:
{
"mcpServers": {
"mcp-mermaid": {
"command": "npx",
"args": [
"-y",
"mcp-mermaid"
]
}
}
}В системе Windows:
{
"mcpServers": {
"mcp-mermaid": {
"command": "cmd",
"args": [
"/c",
"npx",
"-y",
"mcp-mermaid"
]
}
}
}Также вы можете использовать его на aliyun, modelscope, glama.ai, smithery.ai или других платформах с протоколами HTTP и SSE.
Точки доступа:
SSE:
http://localhost:3033/sseStreamable:
http://localhost:1122/mcp
Доступные теги Docker:
susuperli/mcp-mermaid:latest- Последняя стабильная версияПросмотреть все доступные теги можно на Docker Hub
🚰 Запуск с транспортом SSE или Streamable
Вариант 1: Глобальная установка
Установите пакет глобально:
npm install -g mcp-mermaidЗапустите сервер с предпочтительным вариантом транспорта:
# For SSE transport (default endpoint: /sse)
mcp-mermaid -t sse
# For Streamable transport with custom endpoint
mcp-mermaid -t streamableВариант 2: Локальная разработка
Если вы работаете с исходным кодом локально:
# Clone and setup
git clone https://github.com/hustcc/mcp-mermaid.git
cd mcp-mermaid
npm install
npm run build
# Run with npm scripts
npm run start:sse # SSE transport on port 3033
npm run start:streamable # Streamable transport on port 1122Точки доступа
Затем вы можете получить доступ к серверу по адресу:
Транспорт SSE:
http://localhost:3033/sseТранспорт Streamable:
http://localhost:1122/mcp(локально) илиhttp://localhost:3033/mcp(глобально)
🎮 Опции CLI
Вы также можете использовать следующие опции CLI при запуске MCP-сервера. Опции команды можно посмотреть, запустив CLI с флагом -h.
MCP Mermaid CLI
Options:
--transport, -t Specify the transport protocol: "stdio", "sse", or "streamable" (default: "stdio")
--port, -p Specify the port for SSE or streamable transport (default: 3033)
--endpoint, -e Specify the endpoint for the transport:
- For SSE: default is "/sse"
- For streamable: default is "/mcp"
--help, -h Show this help message🔨 Разработка
Установите зависимости:
npm installСоберите сервер:
npm run buildЗапуск MCP-сервера
Использование MCP Inspector (для отладки):
npm run startИспользование различных транспортных протоколов:
# SSE transport (Server-Sent Events)
npm run start:sse
# Streamable HTTP transport
npm run start:streamableПрямые команды node:
# SSE transport on port 3033
node build/index.js --transport sse --port 3033
# Streamable HTTP transport on port 1122
node build/index.js --transport streamable --port 1122
# STDIO transport (for MCP client integration)
node build/index.js --transport stdio🐳 Использование Docker
Запустите MCP Mermaid с помощью Docker:
# Pull the image
docker pull susuperli/mcp-mermaid:latest
# Run with SSE transport (default)
docker run -p 3033:3033 susuperli/mcp-mermaid:latest --transport sse
# Run with streamable transport
docker run -p 1122:1122 susuperli/mcp-mermaid:latest --transport streamable --port 1122📄 Лицензия
MIT@hustcc.
Available Tools
1 toolgenerate_mermaid_diagramBInspect
Generate mermaid diagram and chart with mermaid syntax dynamically. Mermaid is a JavaScript based diagramming and charting tool that uses Markdown-inspired text definitions and a renderer to create and modify complex diagrams. The main purpose of Mermaid is to help documentation catch up with development.
| Name | Required | Description | Default |
|---|---|---|---|
| mermaid | Yes | The mermaid diagram syntax used to be generated, such as, graph TD; A-->B; A-->C; B-->D; C-->D;. | |
| theme | No | Theme for the diagram (optional). Default is 'default'. | default |
| backgroundColor | No | Background color for the diagram (optional). Default is 'white'. | white |
| outputType | No | The output type of the diagram. Can be 'base64', 'svg', 'mermaid', 'file', 'svg_url', or 'png_url'. Default is 'base64'. 'base64' returns PNG image as base64 encoded string. 'file' saves the PNG image to disk. The *_url options return public mermaid.ink links for remote-friendly sharing. | base64 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose behavioral traits such as side effects, performance, or limitations. It only broadly states dynamic generation without specifics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, but the second sentence focuses on Mermaid's general purpose rather than the tool's specific behavior. No filler words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description does not explain the output format or how to use the returned data. With no output schema, relying on the outputType parameter is insufficient for complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the parameters are already well-documented. The description adds no additional meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: generating mermaid diagrams and charts dynamically. It explains what Mermaid is, providing context for the tool's functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool or when not to use it. There are no alternatives mentioned, and the description lacks explicit usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.0- Changed
generate_mermaid_diagram3 fields changed- changed
Input schema / properties / outputType / defaultPrevious value: -"png"New value: +"base64" - changed
Input schema / properties / outputType / descriptionPrevious value: -"The output type of the diagram. Can be 'png', 'svg' or 'mermaid'. Default is 'png'."New value: +"The output type of the diagram. Can be 'base64', 'svg', 'mermaid', 'file', 'svg_url', or 'png_url'. Default is 'base64'. 'base64' returns PNG image as base64 encoded string. 'file' saves the PNG image to disk. The *_url options return public mermaid.ink links for remote-friendly sharing." - changed
Input schema / properties / outputType / enumPrevious value: -[ - "png", - "svg", - "mermaid" -]New value: +[ + "base64", + "svg", + "mermaid", + "file", + "svg_url", + "png_url" +]
1 tool update
- First observed
generate_mermaid_diagram
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion between tools. The tool's purpose is clear and stands alone.
Since there is only one tool, naming consistency is not applicable, but the single name follows a clear descriptive pattern.
A single tool for generating Mermaid diagrams is minimal. While it covers the core functionality, the scope feels thin (1 tool) compared to typical MCP servers that handle diagramming workflows.
The tool covers the primary task of generating diagrams, but lacks auxiliary operations such as validation, styling, or export options that would enhance completeness for a diagramming server.
Maintenance
Related MCP Connectors
Create and manage Mermaid.js flowcharts and diagrams with AI agents via MCP.
Generate org charts, MCD/ERD data models, and C4 architecture diagrams — pilot OrgGen AI via MCP.
Render, verify, describe, and safely edit Mermaid diagrams through MCP.
Create workflow, sequence, architecture, and mind map diagrams via AI assistants.
Related MCP Servers
- TypeScriptMIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that converts text inputs into visualized flowcharts, enabling AI clients to generate high-quality Mermaid diagrams directly from natural language descriptions or structured text.12MIT
- FlicenseNot gradedqualityFmaintenanceNarasimhaponnada/mermaid-mcp - AI-powered Mermaid diagram generation with 22+ diagram types including flowcharts, sequence diagrams, class diagrams, ER diagrams, architecture diagrams, state machines, and more. Features 50+ pre-built templates, advanced layout engines, SVG/PNG/PDF exports.53-
- AlicenseNot gradedqualityDmaintenanceEnables automatic generation of UML class diagrams and entity-relationship diagrams from natural language descriptions or structured JSON data. It integrates with MCP agents to create visual representations of code structures and system designs without manual Mermaid coding.8 npm1MIT