Kylin Offline MCP ECharts
An MCP server for generating offline charts using Apache ECharts SVG SSR and rsvg-convert, optimized for Kylin ARM64 with 64KB page size.
README
Kylin Offline MCP ECharts
离线图表 MCP 服务,面向 Kylin ARM64 + 64KB PAGE_SIZE。它使用 Apache ECharts 的纯 JS SVG SSR 能力,再调用系统 rsvg-convert 生成 PNG,不走 @napi-rs/canvas / canvas PNG 渲染路径。
渲染链路
MCP SSE tool call
-> ECharts option
-> echarts.init(null, theme, { renderer: "svg", ssr: true, width, height })
-> chart.renderToSVGString()
-> rsvg-convert --zoom 2 -f png -o chart.png chart.svg
-> /charts/chart_xxx.png
-> JSON text with chartUrl/imageFile/imageFormat/size
本机 Docker 测试
docker build -t kylin-offline-mcp-echarts:local .
docker run --rm -p 7003:7003 -v "$PWD/charts:/app/charts" kylin-offline-mcp-echarts:local
curl http://127.0.0.1:7003/health
SSE 地址:
http://127.0.0.1:7003/sse
同一端口提供:
/sse
/messages
/health
/charts
测试用例
工具:generate_bar_chart
{
"data": "[{\"category\": \"类兴邦\", \"value\": 9.70}, {\"category\": \"肖棋元\", \"value\": 8.52}, {\"category\": \"刘晶晶\", \"value\": 7.37}, {\"category\": \"庄宇飞\", \"value\": 6.97}, {\"category\": \"张兆乾\", \"value\": 6.41}, {\"category\": \"彭子瑞\", \"value\": 5.01}]",
"title": "报销金额排名前六名人员",
"axisXTitle": "人员姓名",
"axisYTitle": "报销金额(万元)"
}
data 既支持数组,也支持上面这种 JSON 字符串。
成功返回文本内容类似:
{
"status": "success",
"chartUrl": "/charts/generate_bar_chart_1780000000000_abcd1234ef.png",
"imageFile": "/app/charts/generate_bar_chart_1780000000000_abcd1234ef.png",
"imageFormat": "png",
"size": {
"width": 800,
"height": 600,
"bytes": 30000,
"zoom": 2
}
}
Kylin ARM64 Release tar
GitHub Actions 工作流:
.github/workflows/release-kylin-arm64.yml
.github/workflows/release-kylin-arm64-page64k.yml
release-kylin-arm64.yml 使用 GitHub 托管 ubuntu-24.04-arm runner 生成 linux/arm64 tar。GitHub 官方文档列出的 ARM64 runner label 包括 ubuntu-24.04-arm,但托管 runner 不能指定 64K page-size 内核。
release-kylin-arm64-page64k.yml 用 [self-hosted, Linux, ARM64, page64k],会先检查:
test "$(uname -m)" = "aarch64"
test "$(getconf PAGE_SIZE)" = "65536"
面向 Kylin ARM64 + 64KB PAGE_SIZE 的最终发布,推荐使用 self-hosted 64K runner workflow。
Kylin 打包默认参考 54dabang/gpt-vis-mcp 的 Kylin 基础镜像:
ARG KYLIN_BASE_IMAGE=macrosan/kylin:v10-sp3-2403
FROM ${KYLIN_BASE_IMAGE}
GitHub Actions 的 kylin_base_image 输入可以覆盖为 kylin-server-arm64:v10。无论使用哪个 Kylin/vendor 基础镜像,都必须先通过 yum 安装 nodejs、npm、gcc、gcc-c++、make、pkgconfig、cairo-devel、libjpeg-turbo-devel、libpng-devel、pango-devel、giflib-devel、librsvg2-devel、librsvg2-tools 等系统依赖,再执行 npm ci。
手动运行时输入 tag,例如 v0.1.0。成功后 Release asset 名称:
kylin-offline-mcp-echarts-v0.1.0-linux-arm64.tar.gz
下载链接模板:
https://github.com/<owner>/<repo>/releases/download/v0.1.0/kylin-offline-mcp-echarts-v0.1.0-linux-arm64.tar.gz
https://gh.llkk.cc/https://github.com/<owner>/<repo>/releases/download/v0.1.0/kylin-offline-mcp-echarts-v0.1.0-linux-arm64.tar.gz
64K 自托管 runner 产物模板:
https://github.com/<owner>/<repo>/releases/download/v0.1.0-page64k/kylin-offline-mcp-echarts-v0.1.0-page64k-linux-arm64-page64k.tar.gz
https://gh.llkk.cc/https://github.com/<owner>/<repo>/releases/download/v0.1.0-page64k/kylin-offline-mcp-echarts-v0.1.0-page64k-linux-arm64-page64k.tar.gz
目标机加载:
docker load -i kylin-offline-mcp-echarts-v0.1.0-linux-arm64.tar.gz
docker image inspect kylin-offline-mcp-echarts:v0.1.0-arm64 --format '{{.Os}}/{{.Architecture}}'
docker run -d --name kylin-offline-mcp-echarts -p 7003:7003 -v "$PWD/charts:/app/charts" kylin-offline-mcp-echarts:v0.1.0-arm64
64KB 页面大小最终仍建议在真实 Kylin ARM64 目标机上确认:
getconf PAGE_SIZE
docker exec kylin-offline-mcp-echarts rsvg-convert --version
curl http://127.0.0.1:7003/health
关键约束
本项目没有运行时依赖 mcp-echarts npm 包,因为 mcp-echarts@0.7.1 直接依赖 @napi-rs/canvas。这里保留兼容的工具定义和 ECharts option 生成方式,但渲染路径完全替换为 SVG SSR + 系统 rsvg-convert。
Dockerfile.kylin 仍设置 64K 链接和 npm 源码编译约束:
ENV LDFLAGS="-Wl,-z,max-page-size=65536"
ENV npm_config_build_from_source=true
ENV npm_config_canvas_build_from_source=true
当前业务路径不调用 canvas,这两个环境变量是为了防止未来依赖变化时误拉 4KB page-size 预编译原生包。
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.