196 lines
5 KiB
TypeScript
196 lines
5 KiB
TypeScript
import { Anthropic } from "@anthropic-ai/sdk";
|
|
import {
|
|
MessageParam,
|
|
Tool,
|
|
} from "@anthropic-ai/sdk/resources/messages/messages.mjs";
|
|
|
|
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
|
|
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
|
|
import readline from "readline/promises";
|
|
|
|
import dotenv from "dotenv";
|
|
|
|
dotenv.config(); // load environment variables from .env
|
|
|
|
const ANTHROPIC_MODEL = "claude-sonnet-4-5";
|
|
const ANTHROPIC_API_KEY = process.env.ANTHROPIC_API_KEY;
|
|
if (!ANTHROPIC_API_KEY) {
|
|
throw new Error("ANTHROPIC_API_KEY is not set");
|
|
}
|
|
|
|
class MCPClient {
|
|
private mcp: Client;
|
|
private anthropic: Anthropic;
|
|
private transport: StdioClientTransport | null = null;
|
|
private tools: Tool[] = [];
|
|
|
|
constructor() {
|
|
// Initialize Anthropic client and MCP client
|
|
this.anthropic = new Anthropic({
|
|
apiKey: ANTHROPIC_API_KEY,
|
|
});
|
|
this.mcp = new Client({ name: "mcp-client-cli", version: "1.0.0" });
|
|
}
|
|
|
|
async connectToServer(serverScriptPath: string) {
|
|
/**
|
|
* Connect to an MCP server
|
|
*
|
|
* @param serverScriptPath - Path to the server script (.py or .js)
|
|
*/
|
|
try {
|
|
// Determine script type and appropriate command
|
|
const isJs = serverScriptPath.endsWith(".js");
|
|
const isPy = serverScriptPath.endsWith(".py");
|
|
if (!isJs && !isPy) {
|
|
throw new Error("Server script must be a .js or .py file");
|
|
}
|
|
const command = isPy
|
|
? process.platform === "win32"
|
|
? "python"
|
|
: "python3"
|
|
: process.execPath;
|
|
|
|
// Initialize transport and connect to server
|
|
this.transport = new StdioClientTransport({
|
|
command,
|
|
args: [serverScriptPath],
|
|
});
|
|
await this.mcp.connect(this.transport);
|
|
|
|
// List available tools
|
|
const toolsResult = await this.mcp.listTools();
|
|
this.tools = toolsResult.tools.map((tool) => {
|
|
return {
|
|
name: tool.name,
|
|
description: tool.description,
|
|
input_schema: tool.inputSchema,
|
|
};
|
|
});
|
|
console.log(
|
|
"Connected to server with tools:",
|
|
this.tools.map(({ name }) => name),
|
|
);
|
|
} catch (e) {
|
|
console.log("Failed to connect to MCP server: ", e);
|
|
throw e;
|
|
}
|
|
}
|
|
|
|
async processQuery(query: string) {
|
|
/**
|
|
* Process a query using Claude and available tools
|
|
*
|
|
* @param query - The user's input query
|
|
* @returns Processed response as a string
|
|
*/
|
|
const messages: MessageParam[] = [
|
|
{
|
|
role: "user",
|
|
content: query,
|
|
},
|
|
];
|
|
|
|
// Initial Claude API call
|
|
const response = await this.anthropic.messages.create({
|
|
model: ANTHROPIC_MODEL,
|
|
max_tokens: 1000,
|
|
messages,
|
|
tools: this.tools,
|
|
});
|
|
|
|
// Process response and handle tool calls
|
|
const finalText = [];
|
|
|
|
for (const content of response.content) {
|
|
if (content.type === "text") {
|
|
finalText.push(content.text);
|
|
} else if (content.type === "tool_use") {
|
|
// Execute tool call
|
|
const toolName = content.name;
|
|
const toolArgs = content.input as { [x: string]: unknown } | undefined;
|
|
|
|
const result = await this.mcp.callTool({
|
|
name: toolName,
|
|
arguments: toolArgs,
|
|
});
|
|
finalText.push(
|
|
`[Calling tool ${toolName} with args ${JSON.stringify(toolArgs)}]`,
|
|
);
|
|
|
|
// Continue conversation with tool results
|
|
messages.push({
|
|
role: "user",
|
|
content: result.content as string,
|
|
});
|
|
|
|
// Get next response from Claude
|
|
const response = await this.anthropic.messages.create({
|
|
model: ANTHROPIC_MODEL,
|
|
max_tokens: 1000,
|
|
messages,
|
|
});
|
|
|
|
finalText.push(
|
|
response.content[0].type === "text" ? response.content[0].text : "",
|
|
);
|
|
}
|
|
}
|
|
|
|
return finalText.join("\n");
|
|
}
|
|
|
|
async chatLoop() {
|
|
/**
|
|
* Run an interactive chat loop
|
|
*/
|
|
const rl = readline.createInterface({
|
|
input: process.stdin,
|
|
output: process.stdout,
|
|
});
|
|
|
|
try {
|
|
console.log("\nMCP Client Started!");
|
|
console.log("Type your queries or 'quit' to exit.");
|
|
|
|
while (true) {
|
|
const message = await rl.question("\nQuery: ");
|
|
if (message.toLowerCase() === "quit") {
|
|
break;
|
|
}
|
|
const response = await this.processQuery(message);
|
|
console.log("\n" + response);
|
|
}
|
|
} finally {
|
|
rl.close();
|
|
}
|
|
}
|
|
|
|
async cleanup() {
|
|
/**
|
|
* Clean up resources
|
|
*/
|
|
await this.mcp.close();
|
|
}
|
|
}
|
|
|
|
async function main() {
|
|
if (process.argv.length < 3) {
|
|
console.log("Usage: node build/index.js <path_to_server_script>");
|
|
return;
|
|
}
|
|
const mcpClient = new MCPClient();
|
|
try {
|
|
await mcpClient.connectToServer(process.argv[2]);
|
|
await mcpClient.chatLoop();
|
|
} catch (e) {
|
|
console.error("Error:", e);
|
|
await mcpClient.cleanup();
|
|
process.exit(1);
|
|
} finally {
|
|
await mcpClient.cleanup();
|
|
process.exit(0);
|
|
}
|
|
}
|
|
|
|
main();
|