yutori-mcp 0.2.1

MCP server for Yutori - web monitoring, deep research, and browser automation

Yutori MCP Server & Plugin

An MCP server and Claude Code plugin for Yutori - web monitoring and browsing automation.

Features

• Scouts: Create agents that that monitor the web for anything you care about at a desired frequency
• Research: Execute one-time deep web research tasks
• Browsing: Execute one-time web browsing tasks using an AI website navigator (or a browser-use AI agent)

Installation

If you don't already have uv installed, install it (it includes uvx):

curl -LsSf https://astral.sh/uv/install.sh | sh

Or with Homebrew:

brew install uv

Authenticate

Run this once to install and log in to your Yutori account:

uvx yutori-mcp login

This opens your browser, authenticates with Yutori, and saves an API key locally (~/.yutori/config.json). All platforms below will use this saved key automatically.

Choose your platform

Claude Code

1. Plugin (Recommended) - Includes MCP tools + workflow skills

   Run these commands inside Claude Code:

   /plugin marketplace add yutori-ai/yutori-mcp
   /plugin install yutori@yutori-plugins
   

   Skill	Description
   /yutori:scout	Set up continuous web monitoring with comprehensive queries
   /yutori:research	Deep web research workflow (async, 5-10 min)
   /yutori:browse	Browser automation tasks
   /yutori:competitor-watch	Quick competitor monitoring template
   /yutori:api-monitor	API/changelog monitoring template

   Already have the MCP server installed? Remove it first to avoid duplicate configurations:

   claude mcp remove yutori -s user   # if installed at user scope
   claude mcp remove yutori -s local  # if installed at local/project scope
   

2. MCP Only (if you prefer not to use the plugin)

   claude mcp add --scope user yutori -- uvx yutori-mcp
   

   Or pass your API key explicitly instead of logging in:

   claude mcp add --scope user yutori --env YUTORI_API_KEY=yt-your-api-key -- uvx yutori-mcp
   

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "yutori": {
      "command": "uvx",
      "args": ["yutori-mcp"]
    }
  }
}

Or pass your API key explicitly via env var:

{
  "mcpServers": {
    "yutori": {
      "command": "uvx",
      "args": ["yutori-mcp"],
      "env": {
        "YUTORI_API_KEY": "yt-your-api-key"
      }
    }
  }
}

For setup details, see the Claude Desktop MCP install guide.

Cursor

Click the button to install:

Or install manually:

Go to Cursor Settings → MCP → Add new MCP Server, then add:

{
  "mcpServers": {
    "yutori": {
      "command": "uvx",
      "args": ["yutori-mcp"]
    }
  }
}

See the Cursor MCP guide for setup details.

VS Code

Click the button to install:

Or install manually:

code --add-mcp '{"name":"yutori","command":"uvx","args":["yutori-mcp"]}'

ChatGPT

Open ChatGPT Desktop and go to Settings -> Connectors -> MCP Servers -> Add server.

{
  "mcpServers": {
    "yutori": {
      "command": "uvx",
      "args": ["yutori-mcp"]
    }
  }
}

For setup details, see the OpenAI MCP guide.

Codex

1. MCP Server:

   codex mcp add yutori -- uvx yutori-mcp
   

   Or add to ~/.codex/config.toml:

   [mcp_servers.yutori]
   command = "uvx"
   args = ["yutori-mcp"]
   

2. Skills (optional, for workflow guidance):

   Install skills using $skill-installer inside Codex:

   $skill-installer install https://github.com/yutori-ai/yutori-mcp/tree/main/.agents/skills/yutori-scout
   $skill-installer install https://github.com/yutori-ai/yutori-mcp/tree/main/.agents/skills/yutori-research
   $skill-installer install https://github.com/yutori-ai/yutori-mcp/tree/main/.agents/skills/yutori-browse
   $skill-installer install https://github.com/yutori-ai/yutori-mcp/tree/main/.agents/skills/yutori-competitor-watch
   $skill-installer install https://github.com/yutori-ai/yutori-mcp/tree/main/.agents/skills/yutori-api-monitor
   

   Or manually copy skills to your user directory (use -L so symlinks are dereferenced and real files are copied):

   git clone https://github.com/yutori-ai/yutori-mcp /tmp/yutori-mcp
   cp -rL /tmp/yutori-mcp/.agents/skills/* ~/.agents/skills/
   

   Restart Codex after installing skills.

   Skill	Command	Description
   Scout	$yutori-scout	Set up continuous web monitoring
   Research	$yutori-research	Deep web research (async, 5-10 min)
   Browse	$yutori-browse	Browser automation with AI navigator
   Competitor Watch	$yutori-competitor-watch	Quick competitor monitoring template
   API Monitor	$yutori-api-monitor	API/changelog monitoring template

   See the Codex Skills docs for more on skills.

Gemini CLI

Add to ~/.gemini/settings.json:

{ ...file contains other config objects
  "mcp": {
    "allowed": ["yutori", "...other MCPs you already allow..."]
  },
  ...file contains other config objects
  "mcpServers": {
    "yutori": {
      "command": "uvx",
      "args": ["yutori-mcp"]
    }
  }
}

For more details, see the Gemini CLI MCP settings guide.

Using pip

pip install yutori-mcp

Tools

All tool outputs are formatted as human-readable text optimized for LLM consumption.

Scout Tools

list_scouts

List scouts for the user with optional filtering.

{
  "limit": 10,
  "status": "active"
}

Parameter	Required	Description
limit	No	Max scouts to return (1-100). Default: 10
status	No	Filter by active, paused, or done

Example response:

Found 87 scouts: 72 active, 12 paused, 3 done.

Showing 10 of 87:

1. Yutori news and updates (active)
   Query: "Tell me about the latest news, product updates, or..."
   ID: 690bd26c-0ef8-42f4-99e4-8fca6ea20e6f
   Runs daily | Next: 2026-01-16

2. Yutori API changelog (paused)
   Query: "Monitor Yutori API changelog for breaking changes"
   ID: 36d178a0-591f-4567-8019-32d24f9e55ba
   Runs every 12 hours | Next: 2026-01-10

... (8 more)

Use list_scouts(status="active") to filter by status.
Use list_scouts(limit=50) to see more.
Use get_scout_detail(scout_id) for full details.

get_scout_detail

Get detailed information for a specific scout.

{
  "scout_id": "690bd26c-0ef8-42f4-99e4-8fca6ea20e6f"
}

Example response:

Scout: Yutori news and updates
ID: 690bd26c-0ef8-42f4-99e4-8fca6ea20e6f
Status: active

Query: "Tell me about the latest news, product updates, or announcements about Yutori"

Schedule:
  Interval: daily
  Next run: 2026-01-16 18:32 UTC
  Timezone: America/Los_Angeles

Configuration:
  Webhook: not configured
  Email notifications: enabled
  Public: yes

Created: 2026-01-15

create_scout

Create a new monitoring scout for continuous web monitoring. Scouts track changes relevant to a query at a configurable schedule and alert you with structured data.

Basic example:

{
  "query": "Tell me about the latest news, product updates, press releases, social media announcements, investments into, or other relevant information about Yutori"
}

Advanced example (scheduling, webhooks, structured output):

{
  "query": "Tell me about the latest news, product updates, press releases, social media announcements, investments into, or other relevant information about Yutori",
  "output_interval": 86400,
  "user_timezone": "America/Los_Angeles",
  "skip_email": true,
  "webhook_url": "https://example.com/webhook",
  "output_fields": ["headline", "summary", "source_url"]
}

Example response:

Scout created successfully.

Name: Yutori news and updates
ID: 3d1d5e2a-5b6c-4a9c-8f8c-2f2e3b4a5c6d
Status: active

Query: "Tell me about the latest news, product updates, press releases, social..."
Schedule: runs daily
First run: 2026-01-07 03:10 UTC

Parameter	Required	Description
query	Yes	Natural language description of what to monitor
output_interval	No	Seconds between runs (min: 1800). Default: 86400
webhook_url	No	URL for webhook notifications
webhook_format	No	scout (default), slack, or zapier
output_fields	No	List of field names for structured output as array of objects
user_timezone	No	Timezone for scheduling
skip_email	No	Skip email notifications
start_timestamp	No	Unix timestamp for when monitoring should start (0 = immediately)
user_location	No	Location for geo-relevant searches
is_public	No	Whether scout results are publicly accessible

edit_scout

Update an existing scout's query, schedule, webhook configuration, or status.

Change status only (pause a scout):

{
  "scout_id": "abc123-...",
  "status": "paused"
}

Update configuration:

{
  "scout_id": "abc123-...",
  "output_interval": 43200,
  "user_timezone": "America/New_York"
}

Update configuration and resume:

{
  "scout_id": "abc123-...",
  "query": "updated monitoring query",
  "status": "active"
}

Example response:

Scout updated successfully.

Name: Yutori API changelog
ID: 7c8692c3-c637-4302-a982-b9f4f7b49407

Changes applied:
  • Status: paused → active
  • Query: "Monitor Yutori API changelog..." → "updated monitoring query"

Parameter	Required	Description
scout_id	Yes	Scout UUID
status	No	active (resume), paused (pause), or done (archive)
query	No	Updated monitoring query
output_interval	No	Seconds between runs (min 1800)
webhook_url	No	Webhook notification URL
webhook_format	No	scout, slack, or zapier
output_fields	No	List of field names for structured output
user_timezone	No	Timezone for scheduling
user_location	No	Location for geo-relevant searches
skip_email	No	Skip email notifications

delete_scout

Permanently delete a scout. This cannot be undone.

{
  "scout_id": "abc123-..."
}

Example response:

Scout deleted.

ID: abc123-...

This action cannot be undone.

get_scout_updates

Get paginated updates from a scout.

{
  "scout_id": "690bd26c-0ef8-42f4-99e4-8fca6ea20e6f",
  "limit": 2
}

Example response:

Found 2 update(s):

--- Update #1 —
Date: 2026-01-16 05:45 UTC

Yutori Product Updates

Yutori has released new MCP server tools for web monitoring and browsing automation...

--- Update #2 —
Date: 2026-01-15 05:45 UTC

No new findings since last update.

Research Tools

run_research_task

Execute a one-time deep web research task. The research agent searches, reads, and synthesizes information from across the web.

Basic example:

{
  "query": "What are the latest developments in quantum computing from the past week? Include company announcements, research papers, and product releases."
}

Advanced example (webhooks, structured output):

{
  "query": "What are the latest developments in quantum computing from the past week? Include company announcements, research papers, and product releases.",
  "user_timezone": "America/Los_Angeles",
  "webhook_url": "https://example.com/webhook",
  "output_fields": ["title", "summary", "source_url", "category"]
}

Example response:

Research task started.

Task ID: ae27a17c-a4ed-4c69-8b2a-4bec330fc935-1768848395
Status: queued
View progress: https://scouts.yutori.com/ae27a17c-a4ed-4c69-8b2a-4bec330fc935

Poll with get_research_task_result(task_id="ae27a17c-a4ed-4c69-8b2a-4bec330fc935-1768848395") to check status.

Parameter	Required	Description
query	Yes	Natural language description of what to research
user_timezone	No	Timezone for context. Default: 'America/Los_Angeles'
user_location	No	Location for context. Default: 'San Francisco, CA, US'
output_fields	No	List of field names for structured output as array of objects
webhook_url	No	URL for completion notification
webhook_format	No	scout (default), slack, or zapier

get_research_task_result

Poll for the status and result of a research task. Call this after run_research_task until status is succeeded or failed.

{
  "task_id": "ae27a17c-a4ed-4c69-8b2a-4bec330fc935-1768848395"
}

Example response (running):

Task in progress.

Task ID: ae27a17c-a4ed-4c69-8b2a-4bec330fc935-1768848395
Status: running

Poll again in a few seconds.

Example response (succeeded):

Task completed.

Task ID: ae27a17c-a4ed-4c69-8b2a-4bec330fc935-1768848395
Status: succeeded

Result:
Hardware strides and strategic moves this week

I focused on notable hardware breakthroughs, leadership changes, applied research,
and an industry appearance from January 12–19, 2026.

• MIT demonstrated chip-based cooling for trapped-ion qubits
• EeroQ unveiled a scalable quantum control chip
• IonQ appointed Katie Arrington as Chief Information Officer
• Researchers introduced QUPID, a quantum neural network

Browsing Tools

run_browsing_task

Execute a one-time web browsing task using the navigator agent. The agent runs a cloud browser and operates it like a person - clicking, typing, scrolling, and navigating for you.

Basic example:

{
  "task": "Give me a list of all employees (names and titles) of Yutori.",
  "start_url": "https://yutori.com"
}

Advanced example (webhooks, structured output):

{
  "task": "Give me a list of all employees (names and titles) of Yutori.",
  "start_url": "https://yutori.com",
  "max_steps": 75,
  "webhook_url": "https://example.com/webhook",
  "output_fields": ["name", "title"]
}

Example response:

Browsing task started.

Task ID: 54fb19fd-277e-4098-ab72-5a9f8a4347fc-1768848396
Status: queued
View progress: https://scouts.yutori.com/54fb19fd-277e-4098-ab72-5a9f8a4347fc

Poll with get_browsing_task_result(task_id="54fb19fd-277e-4098-ab72-5a9f8a4347fc-1768848396") to check status.

Parameter	Required	Description
task	Yes	Natural language instruction for the navigator
start_url	Yes	URL where browsing begins
max_steps	No	Max browser actions (1-100). Default: 25
output_fields	No	List of field names for structured output as array of objects
webhook_url	No	URL for completion notification
webhook_format	No	scout (default) or slack

get_browsing_task_result

Poll for the status and result of a browsing task. Call this after run_browsing_task until status is succeeded or failed.

{
  "task_id": "54fb19fd-277e-4098-ab72-5a9f8a4347fc-1768848396"
}

Example response (running):

Task in progress.

Task ID: 54fb19fd-277e-4098-ab72-5a9f8a4347fc-1768848396
Status: running

Poll again in a few seconds.

Example response (succeeded):

Task completed.

Task ID: 54fb19fd-277e-4098-ab72-5a9f8a4347fc-1768848396
Status: succeeded

Result:
Summary of All Yutori Employees

I have successfully located all employees of Yutori on their company page.
Here is the complete list of 17 employees with their names and titles:

Founders & Leadership:
1. Abhishek Das - Co-founder and Co-CEO
2. Devi Parikh - Co-founder and Co-CEO
3. Dhruv Batra - Co-founder and Chief Scientist

Executive:
4. Kristi Edleson - Chief of Staff

Technical Staff:
5. Rui Wang - Member of Technical Staff
... (17 employees total)

Source Page: https://yutori.com/company#team

Tool Annotations

Tools include hints for client behavior:

Tool	Annotation
list_scouts, get_scout_detail, get_scout_updates, get_browsing_task_result, get_research_task_result	readOnlyHint: true
edit_scout	idempotentHint: true
delete_scout	destructiveHint: true

Development

Setup

git clone https://github.com/yutori-ai/yutori-mcp
cd yutori-mcp
pip install -e ".[dev]"

Testing

pytest

Running locally

yutori-mcp login    # authenticate (one-time)
python -m yutori_mcp.server

Debugging with MCP Inspector

npx @modelcontextprotocol/inspector yutori-mcp

API Documentation

For full API documentation, visit docs.yutori.com.

License

Apache 2.0