{"id":"mcp-mermaid","name":"MCP Mermaid","homepage":"https://github.com/hustcc/mcp-mermaid","repo_url":"https://github.com/hustcc/mcp-mermaid","category":"developer-tools","subcategories":["diagramming","visualization","documentation"],"tags":["mermaid","diagrams","charts","svg","png","visualization","flowchart","sequence-diagram","npm"],"what_it_does":"MCP server that generates Mermaid diagrams and charts dynamically from AI-generated Mermaid syntax, supporting export as SVG, PNG, base64, or shareable mermaid.ink URLs with configurable themes and backgrounds.","use_cases":["Generate architecture diagrams, flowcharts, or sequence diagrams from natural language descriptions","Export AI-designed system diagrams as PNG files for documentation or presentations","Create shareable diagram links via mermaid.ink without installing local rendering tools","Validate and iterate on Mermaid syntax with AI feedback from the validation tool","Produce ER diagrams, Gantt charts, or class diagrams inline in AI-assisted documentation workflows"],"not_for":["Complex data visualizations requiring D3.js or custom chart libraries (Mermaid syntax limitations apply)","Interactive or animated diagrams (static output only)","Users needing raster image formats beyond PNG (e.g., TIFF, WebP)"],"best_when":"An AI agent needs to produce a visual diagram artifact (architecture, flow, sequence) as part of a documentation or design workflow, and Mermaid's diagram types cover the use case.","avoid_when":"You need pixel-perfect custom visualizations, interactive charts, or diagram types not supported by Mermaid (e.g., network topology maps, infographics).","alternatives":["mcp-d3","mcp-plantuml","excalidraw-api"],"af_score":72.6,"security_score":72.0,"reliability_score":null,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":"latest","last_evaluated":"2026-03-01T09:50:05.876713+00:00","performance":{"latency_p50_ms":null,"latency_p99_ms":null,"uptime_sla_percent":null,"rate_limits":null,"data_source":"llm_estimated","measured_on":null}}