Manus AI - AI Agent Applications Tool

Overview

Manus AI is an autonomous, production-grade AI agent platform that plans, executes and delivers multi-step work products (reports, code, data analysis, web research and more) inside sandboxed virtual computers. Unlike conversational LLMs that return text, Manus runs persistent agent executions that can browse the web, run shell commands, install and run code, manipulate files, and produce final artifacts — all orchestrated via an API, web app, and connectors. ([manus.im](https://manus.im/docs)) Since its public debut in 2025 Manus has been positioned as a benchmark-leading agent with multi-modal input, advanced tool integration (browsers, IDEs, database connectors, Gmail/Notion/Calendar integrations), and configurable agent profiles (e.g., manus-1.6, manus-1.6-lite, manus-1.6-max) for different cost/effort trade-offs. The platform exposes a REST API (POST /v1/tasks, GET /v1/tasks/{id}), webhooks for live progress, and SDK/connector support for common apps. Recent industry coverage also reports that Meta acquired Manus in late 2025, a development that signals its intended integration into Meta’s AI products while Manus continues to operate from Singapore. ([open.manus.ai](https://open.manus.ai/docs/api-reference/create-task))

Key Features

• Autonomous agent mode: plans, executes and finishes multi-step workflows without step-by-step prompting.
• Sandboxed virtual computers that can browse, run code, and manipulate files persistently.
• Rich connectors: Gmail, Notion, Google Calendar, Slack and data integrations for production workflows.
• REST API + webhooks for programmatic task creation, progress events, and result retrieval.
• Configurable agent profiles (manus-1.6, lite, max) for performance and cost trade-offs.

Example Usage

Example (python):

import time
import requests

# Simple example: create a Manus task and poll until completion.
# Based on Manus API quickstart / tasks docs: https://open.manus.ai/docs/quickstart and https://open.manus.ai/docs/api-reference/create-task

API_KEY = "YOUR_MANUS_API_KEY"
BASE = "https://api.manus.ai/v1"

headers = {
    "API_KEY": API_KEY,
    "accept": "application/json",
    "content-type": "application/json",
}

# 1) Create a task (agent mode, using manus-1.6 profile)
create_payload = {
    "prompt": "Research the top 3 competitors for Acme Corp and produce a 500-word competitive brief with citations.",
    "agentProfile": "manus-1.6",
    "taskMode": "agent"
}
resp = requests.post(f"{BASE}/tasks", json=create_payload, headers=headers)
resp.raise_for_status()
task = resp.json()
task_id = task.get("task_id")
print(f"Created task: {task_id}")

# 2) Poll the task until status becomes completed/failed (GET /v1/tasks/{task_id})
while True:
    r = requests.get(f"{BASE}/tasks/{task_id}", headers={"API_KEY": API_KEY, "accept": "application/json"})
    r.raise_for_status()
    info = r.json()
    status = info.get("status")
    print(f"Status: {status}")
    if status in ("completed", "failed"):
        break
    time.sleep(5)

# 3) Show outputs
if info.get("output"):
    for message in info["output"]:
        for part in message.get("content", []):
            if part.get("type") == "output_text":
                print("---\n", part.get("text"))

# For production, use webhooks (open.manus.ai/docs/webhooks) to receive completion events instead of polling.

Pricing

Manus operates a freemium, credit-based subscription model (free tier with daily/bonus credits, paid tiers for higher monthly credits and concurrent tasks). Public reporting and third‑party pricing aggregators list plans in ranges such as Basic/Starter around $19–$39/month and Pro around $199/month, plus team/seat plans and top‑up credits; Manus’s official pricing page is the canonical source for live plan details. See Manus pricing and third‑party summaries. ([manus.im](https://manus.im/pricing))

Benchmarks

GAIA benchmark (reported): Manus reported as state-of-the-art on GAIA (blog cites >65%; later reporting references Level‑1 ~86.5% in some evaluations) (Source: https://huggingface.co/blog/LLMhacker/manus-ai-best-ai-agent and https://almcorp.com/blog/meta-acquires-manus-ai-acquisition-analysis/)

Virtual sandboxes created (company-reported): Reported >80 million virtual computers created for tasks (Source: https://almcorp.com/blog/meta-acquires-manus-ai-acquisition-analysis/)

Tokens processed (company-reported): Reported ~147 trillion tokens processed (Source: https://almcorp.com/blog/meta-acquires-manus-ai-acquisition-analysis/)

Tool integrations: Reported 29+ built-in connectors / tools (Source: https://almcorp.com/blog/meta-acquires-manus-ai-acquisition-analysis/ and https://open.manus.ai/docs)

Key Information

• Category: Agent Applications
• Type: AI Agent Applications Tool