Agent Toolkit

// Set up an MCP server with the Agent Toolkit
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { RecallAgentToolkit } from "@recallnet/agent-toolkit/mcp";
import { Configuration } from "@recallnet/agent-toolkit/shared";
 
// Initialize the toolkit with permissions
const toolkit = new RecallAgentToolkit({
  privateKey: process.env.RECALL_PRIVATE_KEY,
  configuration: {
    actions: {
      account: { read: true },
      bucket: { read: true, write: true },
    },
    context: {},
  },
});
 
// Connect to a transport (typically stdin/stdout)
const transport = new StdioServerTransport();
await toolkit.connect(transport);

// LangChain integration example
import {
  ChatPromptTemplate,
  HumanMessagePromptTemplate,
  MessagesPlaceholder,
  SystemMessagePromptTemplate,
} from "@langchain/core/prompts";
import { ChatOpenAI } from "@langchain/openai";
import { RecallAgentToolkit } from "@recallnet/agent-toolkit/langchain";
import { AgentExecutor, createOpenAIFunctionsAgent } from "langchain/agents";
 
// Create the toolkit
const toolkit = new RecallAgentToolkit({
  privateKey: process.env.RECALL_PRIVATE_KEY,
  configuration: {
    actions: {
      account: { read: true },
      bucket: { read: true, write: true },
    },
    context: {},
  },
});
 
// Get LangChain tools from the toolkit
const recallTools = toolkit.getTools();
 
// Create a prompt template for the agent
const prompt = ChatPromptTemplate.fromMessages([
  SystemMessagePromptTemplate.fromTemplate(
    "You are a helpful assistant with access to Recall storage capabilities. " +
      "1. You can create and manage storage buckets\n" +
      "2. You can store and retrieve information in buckets\n" +
      "3. You can handle both text and binary data\n"
  ),
  new MessagesPlaceholder("agent_scratchpad"),
  HumanMessagePromptTemplate.fromTemplate("{input}"),
]);
 
// Create the agent
const model = new ChatOpenAI({ model: "gpt-4o" });
const agent = await createOpenAIFunctionsAgent({
  llm: model,
  tools: recallTools,
  prompt: prompt,
});
 
// Run the agent
const executor = new AgentExecutor({ agent, tools: recallTools });
const result = await executor.invoke({
  input: "Create a bucket named 'memories' and store today's weather.",
});