LangChain

Wrap myagentmail endpoints as LangChain tools (TS or Python).

TypeScript (LangChain.js)

import { DynamicStructuredTool } from "@langchain/core/tools";
import { z } from "zod";

const KEY = process.env.MYAGENTMAIL_KEY!;
const API = "https://myagentmail.com/v1";

async function mam(method: string, path: string, body?: unknown) {
  const r = await fetch(`${API}${path}`, {
    method,
    headers: { "X-API-Key": KEY, "Content-Type": "application/json" },
    body: body ? JSON.stringify(body) : undefined,
  });
  if (!r.ok) throw new Error(`${method} ${path} → ${r.status}`);
  return r.json();
}

export const sendEmailTool = new DynamicStructuredTool({
  name: "send_email",
  description: "Send an email from a specific myagentmail inbox.",
  schema: z.object({
    inboxId: z.string(),
    to: z.string().email(),
    subject: z.string(),
    plainBody: z.string(),
  }),
  func: async ({ inboxId, ...body }) =>
    JSON.stringify(await mam("POST", `/inboxes/${inboxId}/send`, { ...body, verified: true })),
});

export const listInboxMessagesTool = new DynamicStructuredTool({
  name: "list_inbox_messages",
  description: "List inbound messages in a myagentmail inbox.",
  schema: z.object({
    inboxId: z.string(),
    limit: z.number().int().default(10),
  }),
  func: async ({ inboxId, limit }) =>
    JSON.stringify(await mam("GET", `/inboxes/${inboxId}/messages?direction=inbound&limit=${limit}`)),
});

Python (LangChain)

import os, requests
from langchain_core.tools import tool

KEY = os.environ["MYAGENTMAIL_KEY"]
API = "https://myagentmail.com/v1"
H   = {"X-API-Key": KEY, "Content-Type": "application/json"}

def mam(method, path, body=None):
    r = requests.request(method, f"{API}{path}", headers=H, json=body)
    r.raise_for_status()
    return r.json()

@tool
def send_email(inbox_id: str, to: str, subject: str, plain_body: str) -> dict:
    """Send an email from a myagentmail inbox."""
    return mam("POST", f"/inboxes/{inbox_id}/send",
               {"to": to, "subject": subject, "plainBody": plain_body, "verified": True})

@tool
def list_inbox_messages(inbox_id: str, limit: int = 10) -> dict:
    """List recent inbound messages in a myagentmail inbox."""
    return mam("GET", f"/inboxes/{inbox_id}/messages?direction=inbound&limit={limit}")

Pass these tools into your agent constructor (create_react_agent, AgentExecutor, LangGraph node, etc.) and the LLM will call them when relevant.