MCP Servers

rnaseq-plot-mcp

MCP server for RNA-seq downstream analysis, wrapping R scripts to generate plots and perform analyses like PCA, volcano, heatmap, enrichment, and WGCNA.

README

rnaseq-plot-mcp

RNA-seq 下游出图 / 分析 MCP（旧称 rgraph）。把一套参数化 R 出图脚本（ggplot2 / pheatmap / clusterProfiler / edgeR / limma / WGCNA …）封装为 MCP 工具，由本机 Rscript 渲染 png + pdf。

吃用户自己的 count / FPKM 表，不捆绑任何物种基因组或表达矩阵。

为什么是「R 引擎 + Python MCP」

忠实：不在 Python 里重画，直接驱动 R。
参数化：无 setwd() 硬编码，输入/输出/阈值/配色走参数。
优雅降级：找不到 Rscript → 返回可手动运行的 .R；缺包 → 返回包名与安装命令。
可复现：--no-init-file --no-site-file，屏蔽用户 .Rprofile 横幅。

R 引擎

优先级：环境变量 RGRAPH_RSCRIPT → PATH 上的 Rscript → C:\Program Files\R\... / 注册表。

$env:RGRAPH_RSCRIPT = "C:\Program Files\R\R-4.5.1\bin\Rscript.exe"
uv run rgraph-cli

数据格式

文件	必需列
`sample_group.csv`	`sample_name`, `group`/`group_name`, `TvsC`(treatment/control)
`gene_count.csv`	`gene_id`, `Length`, 各样本 count
`gene_fpkm.csv` / `gene_tpm.csv`	`gene_id`, 各样本列
差异结果	`gene_id`, `log2FoldChange`, `pvalue`, `padj`

差异基因判定默认用 padj（FDR）。

工具（34）

核心：rgraph_env rgraph_normalize rgraph_correlation rgraph_pca rgraph_distribution rgraph_diff rgraph_volcano rgraph_heatmap rgraph_enrich rgraph_go_plot rgraph_kegg_plot rgraph_ppi rgraph_gsea

高级：韦恩/象限/堆叠火山、WGCNA、网络图、ssGSEA、圈图、桑基、交互火山等。缺 ComplexHeatmap 时热图回退 pheatmap；缺 DESeq2 时可用 edgeR/limma。

WGCNA → 网络：rgraph_wgcna 导出 Cytoscape_edges_*.txt 后交给 rgraph_network(mode="edge")。

注册

{
  "mcpServers": {
    "r-analysis": {
      "command": "uv",
      "args": ["run", "--directory", "/absolute/path/to/rnaseq-plot-mcp", "server.py"],
      "env": { "RGRAPH_RSCRIPT": "/path/to/Rscript" }
    }
  }
}

合成测试矩阵在 tests/data/（g1–g10，不含真实实验数据）。

MCP 工具名仍是 rgraph_*（如 rgraph_volcano），与本机 Cursor 配置兼容。

许可

MIT。

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