Manus MCP
An MCP server that gives Claude Code full programmatic control over Manus.im through the official Manus API v2, implementing all documented endpoints and composite tools for common workflows.
README
Manus MCP
An MCP server that gives Claude Code full programmatic control over Manus.im through the official Manus API v2. Implements all 30 documented endpoints, 3 composite tools for common workflows, and a local webhook receiver with RSA-SHA256 signature verification.
- Status: production-ready (single-user) — v0.1.1
- Language: Python 3.11+
- Transport: stdio (native to Claude Code)
- Base URL:
https://api.manus.ai
Verified coverage (v0.1.1)
| Layer | Metric |
|---|---|
| Unit tests | 60+ (server.py dispatch, webhook ASGI app, secret-leak guard, schema stability) |
| Live e2e tests | 23 (including task.update / sendMessage / confirmAction / agent.update / website.publish) |
| Composite live | 4 (including the F2 reject check) |
| Webhook live e2e | 1 (cloudflared tunnel + receiver + Manus delivery) |
| Manus API endpoints exercised live | 30/30 (graceful skip only when the account lacks the prerequisite — no agents / no website) |
| Coverage | ≥ 80% (gated in CI) |
mypy --strict |
0 errors |
ruff check |
0 errors |
See docs/SECURITY.md and docs/RELEASE.md for the production flow.
What's included
30 direct API wrappers
| Category | Tools |
|---|---|
| Tasks (9) | manus_task_create, manus_task_detail, manus_task_list, manus_task_update, manus_task_stop, manus_task_delete, manus_task_send_message, manus_task_list_messages, manus_task_confirm_action |
| Projects (2) | manus_project_create, manus_project_list |
| Skills (1) | manus_skill_list |
| Agents (3) | manus_agent_list, manus_agent_detail, manus_agent_update |
| Files (3) | manus_file_create, manus_file_detail, manus_file_delete |
| Webhooks (4) | manus_webhook_create, manus_webhook_list, manus_webhook_delete, manus_webhook_public_key |
| Usage (3) | manus_usage_list, manus_usage_team_statistic, manus_usage_team_log |
| Connectors (1) | manus_connector_list |
| Browser (1) | manus_browser_online_list |
| Website (3) | manus_website_status, manus_website_list_checkpoints, manus_website_publish |
3 composite tools
manus_file_upload— creates a presigned URL, uploads the bytes, and waits forstatus=uploaded. Acceptspath,base64, or a publicurl.manus_task_wait— polls a task until it reaches a terminal status (stopped/waiting/error) and returns new messages plus wait details (event_id + response schema).manus_website_publish_and_wait— publishes a site and waits until it becomespublishedorfailed.
3 webhook tools (read from the local SQLite DB)
manus_webhook_events_list— list received events with filters.manus_webhook_events_get— fetch an event byevent_id.manus_webhook_events_clear— delete received events.
Total: 36 MCP tools.
Installation
cd path/to/Manus-MCP
python -m venv .venv
# Windows:
.venv\Scripts\activate
# macOS/Linux:
# source .venv/bin/activate
pip install -e ".[dev]"
API key configuration
Place a .env file in the project root (a .env.example template is provided). Both variable names are accepted:
MANUS_API_KEY=sk-...
# or, for backwards compatibility:
# ManusAPI=sk-...
Priority: process.env > .env.
Optional settings:
MANUS_BASE_URL=https://api.manus.ai
MANUS_HTTP_TIMEOUT=60
MANUS_LOG_LEVEL=INFO
Registering with Claude Code
Add the following to .claude/settings.json (project-level) or ~/.claude/settings.json (global):
{
"mcpServers": {
"manus": {
"command": "python",
"args": ["-m", "manus_mcp"],
"cwd": "path/to/Manus-MCP"
}
}
}
If MANUS_API_KEY is not set globally, pass it explicitly:
{
"mcpServers": {
"manus": {
"command": "python",
"args": ["-m", "manus_mcp"],
"cwd": "path/to/Manus-MCP",
"env": { "MANUS_API_KEY": "sk-..." }
}
}
}
Restart Claude Code — the manus_* tools will appear in the tool list.
Verification
Without launching the server:
python scripts/list_tools.py
Against the real API:
python scripts/smoke.py
Unit tests:
pytest
Lint and types:
ruff check .
mypy manus_mcp
Usage examples from Claude Code
manus_task_create { "message": { "content": "Give me a 5-bullet summary of today's AI news" } }
The response contains a task_id. Then:
manus_task_wait { "task_id": "<id>", "timeout_sec": 600 }
When it finishes you get last_assistant_message with the final reply and new_messages with the conversation history.
Uploading a file and attaching it to a task:
manus_file_upload { "source": { "path": "C:/docs/report.pdf" } }
manus_task_create {
"message": {
"content": [
{ "type": "text", "text": "Summarize this report" },
{ "type": "file", "file_id": "<file_id>" }
]
}
}
Webhook receiver (optional)
A local receiver for task_created / task_stopped events with full RSA-SHA256 signature verification per ManusAPIDocs/webhooks/security.md.
1. Configure environment variables
MANUS_WEBHOOK_PUBLIC_URL=https://your-tunnel.example.com/manus/webhook
MANUS_WEBHOOK_HOST=127.0.0.1
MANUS_WEBHOOK_PORT=8787
# MANUS_WEBHOOK_DB_PATH=... # defaults to %LOCALAPPDATA%\manus-mcp\events.db on Windows
MANUS_WEBHOOK_PUBLIC_URL must exactly match the URL Manus calls. The Manus signing payload includes this URL, so even a typo will cause every event to be rejected.
2. Start a tunnel
For example, with Cloudflare Tunnel:
cloudflared tunnel --url http://localhost:8787
or ngrok:
ngrok http 8787
3. Run the receiver
python -m manus_mcp.webhook_receiver
# or: manus-mcp-webhook --host 127.0.0.1 --port 8787
4. Register the webhook with Manus
In Claude Code:
manus_webhook_create { "url": "https://your-tunnel.example.com/manus/webhook" }
5. Read events
manus_webhook_events_list { "event_type": "task_stopped", "limit": 20 }
manus_webhook_events_get { "event_id": "..." }
manus_webhook_events_clear { "before_received_at": 1704000000 }
Architecture
manus_mcp/
├── __main__.py # stdio entrypoint
├── server.py # MCP Server bootstrap
├── config.py # pydantic-settings
├── logger.py # stderr-only logger
├── client/
│ ├── manus_client.py # async httpx client + retry
│ ├── rate_limiter.py # per-endpoint token bucket (from rate-limits.md)
│ ├── retry.py # exponential backoff + jitter
│ └── errors.py # ManusApiError / ManusNetworkError
├── schemas/ # pydantic models for each resource (tasks, projects, ...)
├── tools/ # @manus_tool registration for all 36 tools
│ ├── tasks.py projects.py skills.py agents.py
│ ├── files.py webhooks.py usage.py connectors.py
│ ├── browser.py website.py
│ └── composite.py # task_wait / file_upload / website_publish_and_wait
└── webhook_receiver/
├── signature.py # RSA-SHA256 verification using {ts}.{url}.{sha256_hex(body)}
├── storage.py # SQLite WAL
├── server.py # Starlette + uvicorn
├── tools.py # events_list / events_get / events_clear
└── __main__.py
Rate limits
The client honours the API limits (60-second sliding window) and transparently retries 429 responses with backoff + jitter. Limits come from ManusAPIDocs/getting-started/rate-limits.md:
- 10/min:
task.create,task.sendMessage - 40/min: all mutations
- 100/min: all read-only calls
- 600/min:
usage.*
Security
- The API key is never logged.
- The webhook receiver verifies signatures and rejects timestamps older than 5 minutes.
- The public key is cached for 1 hour.
- SQLite is opened in WAL mode with
check_same_thread=Falsefor safe multi-reader access.
License
MIT.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.