Costruire un client MCP personalizzato
Si connetta al server MCP di Synapse dalla propria applicazione utilizzando l'SDK MCP ufficiale.
Costruire un client MCP personalizzato
Se sta costruendo la propria applicazione LLM, può connettersi al server MCP di Synapse direttamente utilizzando l'SDK MCP ufficiale. In questo modo la sua app avrà accesso a tutti i 79 strumenti di Synapse.
SDK
| Linguaggio | Pacchetto |
|---|---|
| TypeScript/JavaScript | @modelcontextprotocol/sdk |
| Python | mcp |
Esempio TypeScript
Installazione
npm install @modelcontextprotocol/sdkConnessione tramite stdio
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);
// List all available tools
const { tools } = await client.listTools();
console.log(`Available tools: ${tools.length}`);
for (const tool of tools) {
console.log(`- ${tool.name}: ${tool.description}`);
}
// Call a tool
const result = await client.callTool({
name: "memory_recall",
arguments: {},
});
console.log(result.content);
// Store a memory
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();Connessione tramite HTTP/SSE (remoto)
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);
// ... use as aboveEsempio Python
Installazione
pip install mcpConnessione tramite stdio
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()
# List tools
tools = await session.list_tools()
print(f"Available tools: {len(tools.tools)}")
# Call a tool
result = await session.call_tool("memory_recall", {})
print(result.content)
# Store a memory
await session.call_tool("memory_store", {
"category": "fact",
"key": "python_client_test",
"content": "Built a Python MCP client",
"tags": ["test", "mcp", "python"],
"priority": "normal",
})Profili degli strumenti
Quando si connette, può richiedere un profilo di strumenti specifico tramite
l'header Mcp-Tool-Profile (HTTP/SSE) o la variabile d'ambiente MCP_PROFILE
(stdio):
// stdio: set env var
env: {
SYNAPSE_MIND_KEY: "mk_...",
MCP_PROFILE: "minimal", // 8 tools instead of 119
}
// HTTP/SSE: set header
requestInit: {
headers: {
Authorization: "Bearer mk_...",
"Mcp-Tool-Profile": "minimal",
},
}Gestione degli errori
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);
}Casi d'uso
- Assistenti AI personalizzati — costruisca il proprio agente con memoria persistente
- Automazione dei flussi di lavoro — concatena strumenti Synapse in flussi personalizzati
- Pipeline di dati — estrae memorie, trasforma, carica altrove
- Dashboard di monitoraggio — visualizza statistiche delle memorie, cronologia chat, attività