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https://github.com/badlogic/pi-mono.git
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8562bcf66a
This adds codemode and MCP support to pi. Codemode (packages/codemode) runs model-written JavaScript in a QuickJS wasm VM inside a worker. From there the script calls pi's tools as async functions, uses a per-session store, and can read the model catalog and run classifiers. The codemode tool in coding-agent is compatible with Codex's exec tool, and codemode.mode works like Codex's tool modes (on or only). Large results are written to a JSON temp file. MCP (packages/mcp) is a standalone client for stdio and streamable HTTP servers, with OAuth. The core only gets general mechanisms; codemode, tool_search and MCP are built-in extensions that use them. Other extensions can replace these built-ins. Tools declare an exposure: direct, model-only, codemode, deferred or hidden. prepareLoadout() lets an orchestrating tool change which tool declarations the model sees. ctx.executeTool() runs nested calls through validation and the tool_call/tool_result hooks. Those calls emit events with parentToolCallId and are recorded as bounded nestedCalls on the parent result, which compaction and HTML export use. Tools can also return structuredContent with an outputSchema, and can report errors with isError instead of throwing. MCP servers come from mcp.json (global, or per project after the project is trusted) or from pi.registerMcpServer(). They are managed with /mcp and pi mcp list|login|logout, and their runtimes load on first use. Closes #10040
50 lines
1.9 KiB
TypeScript
50 lines
1.9 KiB
TypeScript
/**
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* An Agent with the tools of an MCP server plus a codemode tool that calls them from JavaScript.
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*
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* ANTHROPIC_API_KEY=... node packages/agent/examples/mcp-codemode/main.ts \
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* npx -y @modelcontextprotocol/server-filesystem .
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*
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* The arguments are the command that starts a stdio MCP server.
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*/
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import { Agent } from "@earendil-works/pi-agent-core";
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import { createModels } from "@earendil-works/pi-ai";
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import { anthropicProvider } from "@earendil-works/pi-ai/providers/anthropic";
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import { McpClient, StdioTransport } from "@earendil-works/pi-mcp";
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import { createCodemodeTool, createMcpTools, createNestedToolRunner } from "./tools.ts";
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const [command, ...args] = process.argv.slice(2);
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if (!command) {
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console.error("Usage: main.ts <mcp server command> [args...]");
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process.exit(1);
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}
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const models = createModels();
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models.setProvider(anthropicProvider());
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const model = models.getModel("anthropic", "claude-sonnet-4-6");
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if (!model) throw new Error("Model not found");
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const client = new McpClient({ name: "pi-agent-example", version: "1.0.0" });
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await client.connect(new StdioTransport({ command, args }));
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try {
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const agent = new Agent({
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initialState: { systemPrompt: "You are a helpful assistant.", model },
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streamFn: models.streamSimple.bind(models),
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});
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const mcpTools = await createMcpTools(client, "mcp");
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// The model can call the MCP tools directly or batch them in one codemode script.
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agent.state.tools = [...mcpTools, createCodemodeTool(mcpTools, createNestedToolRunner(agent))];
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agent.subscribe((event) => {
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if (event.type === "message_update" && event.assistantMessageEvent.type === "text_delta") {
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process.stdout.write(event.assistantMessageEvent.delta);
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} else if (event.type === "tool_execution_start") {
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console.log(`\n[${event.toolName}]`);
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}
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});
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await agent.prompt("Use codemode to list what the MCP tools can do, then summarize it in two sentences.");
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console.log();
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} finally {
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await client.close();
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}
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