Emil
e196593c84
Autonomous research agent with web search, source analysis, and report synthesis. Built on Pi agent core. Available as CLI, programmatic API, and MCP server. Features: - 4 built-in tools: web_search, read_url, save_note, synthesize_report - CLI with TUI and print modes - Programmatic API via ResearchAgent class - MCP server with 3 tools: research, quick_search, read_url - Skills system for custom research behavior - Automatic .env file loading for API keys - Configurable max turns, output formats (markdown/JSON/bullet) - Automatic report saving to research-output/
60 lines
1.3 KiB
TypeScript
60 lines
1.3 KiB
TypeScript
/**
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* MCP Client Example
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*
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* Demonstrates how to call the research agent MCP server from another agent.
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*
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* Run with:
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* TAVILY_API_KEY=*** \
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* OPENROUTER_API_KEY=*** \
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* npx tsx examples/mcp-client.ts
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*/
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import { Client } from "@modelcontextprotocol/sdk/client/index.js";
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import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
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import { join } from "node:path";
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const mcpServerPath = join(import.meta.dirname, "../dist/mcp-cli.js");
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const transport = new StdioClientTransport({
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command: "node",
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args: [mcpServerPath],
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env: {
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...process.env,
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},
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});
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const client = new Client({
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name: "example-client",
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version: "1.0.0",
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});
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await client.connect(transport);
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console.log("Connected to research agent MCP server\n");
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const toolsResult = await client.listTools();
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console.log("Available tools:");
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for (const tool of toolsResult.tools) {
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console.log(` - ${tool.name}: ${tool.description}`);
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}
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console.log();
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console.log("Starting research on 'Rust async runtime'...\n");
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const result = await client.callTool({
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name: "quick_search",
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arguments: {
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query: "Rust async runtime tokio vs async-std 2026",
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maxResults: 5,
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},
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});
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console.log("Search results:");
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for (const content of result.content) {
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if (content.type === "text") {
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console.log(content.text);
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}
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}
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await client.close();
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