构建自定义 MCP 客户端
使用 MCP SDK 从你自己的应用连接到 Synapse MCP Server。
构建自定义 MCP 客户端
如果你在构建自己的 LLM 应用,可以直接使用官方 MCP SDK 连接到 Synapse MCP Server。这样你的应用就能访问全部 79 个 Synapse 工具。
SDK
| 语言 | 包 |
|---|---|
| TypeScript/JavaScript | @modelcontextprotocol/sdk |
| Python | mcp |
TypeScript 示例
安装
npm install @modelcontextprotocol/sdk通过 stdio 连接
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
const transport = new StdioClientTransport({
command: "npx",
args: ["-y", "synapse-mcp-api@latest"],
env: {
SYNAPSE_MIND_KEY: process.env.SYNAPSE_MIND_KEY!,
SYNAPSE_URL: "https://synapse.schaefer.zone",
},
});
const client = new Client(
{ name: "my-app", version: "1.0.0" },
{ capabilities: {} }
);
await client.connect(transport);
// 列出所有可用工具
const { tools } = await client.listTools();
console.log(`Available tools: ${tools.length}`);
for (const tool of tools) {
console.log(`- ${tool.name}: ${tool.description}`);
}
// 调用工具
const result = await client.callTool({
name: "memory_recall",
arguments: {},
});
console.log(result.content);
// 存储记忆
await client.callTool({
name: "memory_store",
arguments: {
category: "fact",
key: "custom_client_test",
content: "Built a custom MCP client",
tags: ["test", "mcp"],
priority: "normal",
},
});
await client.close();通过 HTTP/SSE 连接(远程)
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { SSEClientTransport } from "@modelcontextprotocol/sdk/client/sse.js";
const transport = new SSEClientTransport(
new URL("https://synapse-mcp.schaefer.zone/sse"),
{
requestInit: {
headers: {
Authorization: `Bearer ${process.env.SYNAPSE_MIND_KEY}`,
},
},
}
);
const client = new Client(
{ name: "my-app", version: "1.0.0" },
{ capabilities: {} }
);
await client.connect(transport);
// ... 同上使用Python 示例
安装
pip install mcp通过 stdio 连接
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
server_params = StdioServerParameters(
command="npx",
args=["-y", "synapse-mcp-api@latest"],
env={
"SYNAPSE_MIND_KEY": "mk_YOUR_KEY",
"SYNAPSE_URL": "https://synapse.schaefer.zone",
},
)
async with stdio_client(server_params) as (read, write):
async with ClientSession(read, write) as session:
await session.initialize()
# 列出工具
tools = await session.list_tools()
print(f"Available tools: {len(tools.tools)}")
# 调用工具
result = await session.call_tool("memory_recall", {})
print(result.content)
# 存储记忆
await session.call_tool("memory_store", {
"category": "fact",
"key": "python_client_test",
"content": "Built a Python MCP client",
"tags": ["test", "mcp", "python"],
"priority": "normal",
})工具配置文件
连接时,可通过 Mcp-Tool-Profile 头(HTTP/SSE)或 MCP_PROFILE 环境变量(stdio)请求特定工具配置文件:
// stdio:设置环境变量
env: {
SYNAPSE_MIND_KEY: "mk_...",
MCP_PROFILE: "minimal", // 8 个工具而非 119 个
}
// HTTP/SSE:设置头
requestInit: {
headers: {
Authorization: "Bearer mk_...",
"Mcp-Tool-Profile": "minimal",
},
}错误处理
try {
const result = await client.callTool({ name: "memory_recall", arguments: {} });
if (result.isError) {
console.error("Tool error:", result.content);
} else {
console.log("Success:", result.content);
}
} catch (err) {
console.error("MCP error:", err);
}用例
- 自定义 AI 助手 — 构建带持久记忆的 Agent
- 工作流自动化 — 在自定义工作流中串联 Synapse 工具
- 数据流水线 — 提取记忆、转换、加载到别处
- 监控仪表板 — 展示记忆统计、聊天历史、任务