mcp_argo_pipeline
Allows scheduling and running Argo WorkflowTemplates through configurable pipelines, with support for authentication and multiple pipeline definitions.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp_argo_pipelinerun sirna pipeline for gene TP53"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp_argo_pipeline — 按 Pipeline 调度 Argo WorkflowTemplate 的 MCP
文件 | 内容 |
| pipeline、templates、instructions、kubeconfig、port、namespace |
| 各 pipeline 多 Bearer(username / unit) |
入口仅 server.py(通过 MCP_PIPELINE 选择流程)。
快速开始
依赖由 uv 管理(pyproject.toml + uv.lock)。
cd mcp/mcp_argo_pipeline
cp pipelines.yaml.example pipelines.yaml
cp auth.yaml.example auth.yaml
uv sync # 生成/更新 .venv(也可交给 start_serve.sh 自动 sync)本地 Cursor(stdio)
{
"mcpServers": {
"argo-sirna": {
"command": ".../mcp/mcp_argo_pipeline/.venv/bin/python",
"args": [".../mcp/mcp_argo_pipeline/server.py"],
"env": { "MCP_PIPELINE": "sirna" }
}
}
}启动时校验 kubeconfig 与模板可访问性;排障可设 MCP_SKIP_STARTUP_CHECKS=1。
服务器
start_serve.sh 启动前会执行 uv sync --frozen(可用 MCP_SKIP_UV_SYNC=1 跳过)。
./start_serve.sh
./start_serve.sh sirna
./start_serve.sh -f enzyme默认端口(见 pipelines.yaml):affinity 8101、sirna 8102、enzyme 8103。
远程客户端(Streamable HTTP)
服务端强制 Authorization: Bearer <token>,token 来自 auth.yaml(示例见 auth.yaml.example)。将下列片段写入 Cursor 的 mcp.json(~/.cursor/mcp.json 或项目 .cursor/mcp.json),按实际主机改 url。
{
"mcpServers": {
"argo-affinity": {
"url": "http://127.0.0.1:8101/mcp",
"headers": {
"Authorization": "Bearer change-me-affinity-alice"
}
},
"argo-sirna": {
"url": "http://127.0.0.1:8102/mcp",
"headers": {
"Authorization": "Bearer change-me-sirna-carol"
}
},
"argo-enzyme": {
"url": "http://127.0.0.1:8103/mcp",
"headers": {
"Authorization": "Bearer change-me-enzyme-dave"
}
}
}
}对应示例身份:alice(结构生物学组)、carol(核酸药物组)、dave(酶工程组)。上线请改掉 change-me-*,勿把真实 token 提交仓库;也可用 "Authorization": "Bearer ${env:ARGO_SIRNA_TOKEN}" 从环境变量注入。
Related MCP server: gitlab-api
pipelines.yaml
pipelines:
sirna:
server_name: argo-sirna
kubeconfig: "~/.kube/config"
port: 8102
instructions: |
...
templates:
- sirna-predict环境变量
变量 | 含义 |
| 当前 pipeline(必填) |
| pipelines.yaml 路径 |
| auth.yaml 路径 |
|
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