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refactor(agent-infra): mcp-client esm to cjs
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11 files changed

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-386
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11 files changed

+341
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‎apps/agent-tars/package.json

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@@ -51,7 +51,7 @@
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"devDependencies": {
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"jsonrepair": "3.12.0",
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"serialize-javascript": "6.0.2",
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"@modelcontextprotocol/sdk": "^1.10.0",
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"@modelcontextprotocol/sdk": "^1.10.2",
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"@electron-toolkit/preload": "^3.0.1",
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"@electron-toolkit/utils": "^4.0.0",
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"@electron/asar": "^3.2.18",

‎apps/agent-tars/src/renderer/package.json

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"path-browserify": "1.0.1"
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},
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"devDependencies": {
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"@modelcontextprotocol/sdk": "^1.10.0",
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"@modelcontextprotocol/sdk": "^1.10.2",
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"typescript": "^5.7.3",
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"@types/react": "^18.3.18",
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"@types/react-dom": "^18.3.5",

‎packages/agent-infra/mcp-client/examples/test.ts

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/*
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* Copyright (c) 2025 Bytedance, Inc. and its affiliates.
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* SPDX-License-Identifier: Apache-2.0
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*/
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import { AzureOpenAI } from 'openai';
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import { MCPClient, MCPTool } from '../src/index';
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import {
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ChatCompletionMessageParam,
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ChatCompletionTool,
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} from 'openai/resources/index.mjs';
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import {
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client as mcpBrowserClient,
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// setInitialBrowser,
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} from '@agent-infra/mcp-server-browser';
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import { client as mcpCommandsClient } from '@agent-infra/mcp-server-commands';
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import {
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client as mcpFilesystemClient,
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setAllowedDirectories,
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} from '@agent-infra/mcp-server-filesystem';
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import path from 'node:path';
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const currentDir = path.join(__dirname, '../');
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const PLANNING_SYSTEM_PROMPT = `
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You are an expert Planning Agent tasked with solving problems efficiently through structured plans.
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Your job is:
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1. Analyze requests to understand the task scope
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2. Create a clear, actionable plan that makes meaningful progress with the \`planning\` tool
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3. Execute steps using available tools as needed
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4. Track progress and adapt plans when necessary
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5. Use \`finish\` to conclude immediately when the task is complete
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Available tools will vary by task but may include:
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- \`planning\`: Create, update, and track plans (commands: create, update, mark_step, etc.)
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- \`finish\`: End the task when complete
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Break tasks into logical steps with clear outcomes. Avoid excessive detail or sub-steps.
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Think about dependencies and verification methods.
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Know when to conclude - don't continue thinking once objectives are met.
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`;
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const NEXT_STEP_PROMPT = `
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Based on the current state, what's your next action?
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Choose the most efficient path forward:
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1. Is the plan sufficient, or does it need refinement?
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2. Can you execute the next step immediately?
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3. Is the task complete? If so, use \`finish\` right away.
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Be concise in your reasoning, then select the appropriate tool or action.
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`;
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const supportedAttributes = [
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'type',
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'nullable',
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'required',
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// 'format',
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'description',
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'properties',
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'items',
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'enum',
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'anyOf',
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];
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function filterPropertieAttributes(tool: MCPTool) {
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const roperties = tool.inputSchema.properties;
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const getSubMap = (obj: Record<string, any>, keys: string[]) => {
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return Object.fromEntries(
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Object.entries(obj).filter(([key]) => keys.includes(key)),
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);
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};
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for (const [key, val] of Object.entries(roperties as any)) {
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// @ts-ignore
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roperties[key] = getSubMap(val as any, supportedAttributes);
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}
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return roperties;
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}
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function mcpToolsToOpenAITools(mcpTools: MCPTool[]): Array<ChatCompletionTool> {
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return mcpTools.map((tool) => ({
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type: 'function',
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function: {
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name: tool.name,
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description: tool.description,
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parameters: {
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type: 'object',
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properties: filterPropertieAttributes(tool),
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},
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},
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}));
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}
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function mcpToolsToAnthropicTools(mcpTools: MCPTool[]): Array<any> {
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return mcpTools.map((tool) => {
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const t = {
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name: tool.id,
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description: tool.description,
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// @ts-ignore no check
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input_schema: tool.inputSchema,
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};
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return t;
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});
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}
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function mcpToolsToAzureTools(mcpTools: MCPTool[]): Array<any> {
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return mcpTools.map((tool) => {
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const t = {
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type: 'function',
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function: {
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name: tool.name,
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description: tool.description,
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// @ts-ignore no check
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parameters: tool.inputSchema,
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},
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};
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return t;
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});
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}
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function toolUseToMcpTool(
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mcpTools: MCPTool[] | undefined,
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toolUse: any,
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): MCPTool | undefined {
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if (!mcpTools) return undefined;
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const tool = mcpTools.find((tool) => tool.name === toolUse.function.name);
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if (!tool) {
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return undefined;
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}
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// @ts-ignore ignore type as it it unknow
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tool.inputSchema = JSON.parse(toolUse.function.arguments);
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return tool;
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}
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(async () => {
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const client = new MCPClient(
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[
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// {
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// name: 'browser',
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// description: 'web browser tools',
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// localClient: mcpBrowserClient,
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// },
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// {
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// name: 'filesystem',
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// description: 'filesystem tools',
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// localClient: mcpFilesystemClient,
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// },
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{
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name: 'add_function',
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description: 'add function',
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type: 'sse',
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url: 'https://6vknhcia.mcp.bytedance.net/sse',
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headers: {
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Authorization: 'Bearer user@example.com:foo:bar',
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},
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},
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// {
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// name: 'filesystem',
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// command: 'npx',
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// args: [
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// '-y',
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// '@agent-infra/mcp-server-filesystem',
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// path.join(__dirname, '../'),
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// ],
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// },
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// {
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// name: 'commands',
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// description: 'commands tools',
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// localClient: mcpCommandsClient,
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// },
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// {
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// name: 'browser',
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// command: 'npx',
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// args: ['-y', '@agent-infra/mcp-server-browser'],
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// },
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],
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{
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isDebug: true,
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},
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);
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// await client.init();
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setAllowedDirectories([currentDir]);
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// setInitialBrowser(your_browser, your_page);
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const tools = await client.listTools();
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console.log('toolstools', tools);
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// const openai = new AzureOpenAI({
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// endpoint: process.env.AZURE_OPENAI_ENDPOINT,
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// apiVersion: process.env.AZURE_OPENAI_API_VERSION,
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// apiKey: process.env.AZURE_OPENAI_API_KEY,
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// });
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// const azureTools = mcpToolsToAzureTools(tools);
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// console.log('azureTools', azureTools);
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// const messages: ChatCompletionMessageParam[] = [
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// {
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// role: 'system',
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// content: PLANNING_SYSTEM_PROMPT,
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// },
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// {
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// role: 'user',
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// content: `将 \"hello world\" 写入到文件 todo.md 中，用户当前目录是 ${currentDir}`,
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// },
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// ];
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// const pcScreenshotName = 'pc_screenshot';
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// while (true) {
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// if (messages.length > 0) {
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// if (messages[messages.length - 1].role === 'tool') {
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// const screenshotResule = await client.callTool({
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// client: 'browser',
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// name: 'browser_screenshot',
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// args: {
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// name: pcScreenshotName,
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// },
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// });
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// messages.push({
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// role: 'user',
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// content: [
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// ...((screenshotResule.content as any).map((item: any) => {
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// if (item.type === 'image') {
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// return {
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// type: 'image_url',
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// image_url: {
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// url: `data:image/png;base64,aaaa`,
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// },
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// };
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// }
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// return item;
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// }) || []),
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// {
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// type: 'text',
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// text: NEXT_STEP_PROMPT,
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// },
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// ],
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// });
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// } else if (messages[messages.length - 1].role === 'assistant') {
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// messages.push({
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// role: 'user',
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// content: NEXT_STEP_PROMPT,
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// });
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// }
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// }
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// console.log('messages', JSON.stringify(messages, null, 4));
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// const response = await openai.chat.completions.create({
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// model: process.env.AZURE_OPENAI_MODEL || '',
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// messages,
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// tools: azureTools,
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// tool_choice: 'auto',
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// max_tokens: 5120,
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// stream: false,
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// });
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// console.log('response.choices', response.choices);
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// const choice = response.choices[0];
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// if (!choice.message) continue;
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// const responseMessage = response.choices[0].message;
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// messages.push({
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// role: responseMessage.role,
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// content: responseMessage.content,
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// });
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// console.log('choice.message', choice.message.tool_calls);
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// if (response.choices.length > 0) {
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// const toolResults = [];
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// for (const responseChoice of response.choices) {
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// for (const toolCall of responseChoice.message?.tool_calls || []) {
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// console.log(
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// `调用函数${toolCall.id}: ${toolCall.function.name}(${toolCall.function.arguments})`,
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// );
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// const mcpTool = toolUseToMcpTool(tools, toolCall);
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// if (mcpTool) {
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// const result = await client.callTool({
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// client: mcpTool?.serverName as 'commands' | 'browser',
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// name: mcpTool?.name,
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// args: mcpTool?.inputSchema,
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// });
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// console.log('result', result);
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// const { content } = result as any;
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// console.log('content', content);
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// toolResults.push({
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// name: mcpTool?.name,
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// role: 'tool' as const,
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// tool_call_id: toolCall.id,
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// content: JSON.stringify(content),
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// });
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// }
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// }
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// }
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// messages.push(...toolResults);
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// console.log('messages_after_tool_call', messages);
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// }
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// }
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await client.cleanup();
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})();

‎packages/agent-infra/mcp-client/package.json

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"version": "0.4.3",
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"description": "An MCP Client to run servers for Electron apps, support same-process approaching",
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"private": false,
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"type": "module",
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"types": "./dist/index.d.ts",
8-
"main": "./dist/index.cjs",
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"module": "./dist/index.js",
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"main": "./dist/index.js",
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"module": "./dist/index.mjs",
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"files": [
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"dist"
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],
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"scripts": {
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"dev": "tsx src/test.ts",
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"dev": "tsx examples/test.ts",
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"clean": "rm -rf dist",
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"build": "rslib build",
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"prepare": "npm run build",
@@ -21,7 +20,7 @@
2120
"test:integration": "vitest tests/integration"
2221
},
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"dependencies": {
24-
"@modelcontextprotocol/sdk": "^1.10.0",
23+
"@modelcontextprotocol/sdk": "^1.10.2",
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"@agent-infra/mcp-shared": "workspace:*",
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"zod": "^3.23.8",
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"uuid": "^11.1.0"

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