Science & Education
用梅森增益公式逐步求解控制系统信号流图：前向通路枚举、回路发现、不接触回路组合、Δ 与 Δk 行列式、精确传递函数。
用三种语言从你的代码中调用此工具。
curl -X POST 'http://127.0.0.1:3003/zh/api/tools/signal-flow-graph-mason-gain-rule-feedback-loop-solver' \
-H 'Content-Type: application/json' \
-d '{"edges":"R -> n1 = 1\nn1 -> n2 = G1\nn2 -> n3 = G2\nn3 -> out = 1\nn1 -> n4 = G3\nn4 -> n3 = G4\nn2 -> n2 = H1\nn4 -> n4 = H2","inputNode":"R","outputNode":"out"}'以 JSON 形式 POST 提交输入参数。文件类型参数需先单独上传。
POST http://127.0.0.1:3003/zh/api/tools/signal-flow-graph-mason-gain-rule-feedback-loop-solver| 参数名 | 类型 | 必填 | 说明 |
|---|---|---|---|
| edges | textarea | 是 | — |
| inputNode | text | 是 | — |
| outputNode | text | 是 | — |
HTML 结果
{
"result": "<div>Processed HTML content</div>",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}将此工具加入你的 Model Context Protocol 服务，让 AI 智能体可以列出并调用它。
将以下内容加入你的 MCP 客户端配置：
{
"mcpServers": {
"elysiatools-signal-flow-graph-mason-gain-rule-feedback-loop-solver": {
"name": "signal-flow-graph-mason-gain-rule-feedback-loop-solver",
"description": "用梅森增益公式逐步求解控制系统信号流图：前向通路枚举、回路发现、不接触回路组合、Δ 与 Δk 行列式、精确传递函数。",
"baseUrl": "http://127.0.0.1:3003/mcp/sse?toolId=signal-flow-graph-mason-gain-rule-feedback-loop-solver",
"command": "",
"args": [],
"env": {},
"isActive": true,
"type": "sse"
}
}
}连接到 SSE 端点后，列出已开放的工具：
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/list"
}通过工具 id 调用，参数由其参数表构建：
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/call",
"params": {
"name": "signal-flow-graph-mason-gain-rule-feedback-loop-solver",
"arguments": {
"edges": "R -> n1 = 1\nn1 -> n2 = G1\nn2 -> n3 = G2\nn3 -> out = 1\nn1 -> n4 = G3\nn4 -> n3 = G4\nn2 -> n2 = H1\nn4 -> n4 = H2",
"inputNode": "R",
"outputNode": "out"
}
}
}有问题或反馈？请联系 [email protected]