Kinescope MCP Server

Kinescope MCP Server is a server implementing the Model Context Protocol (MCP), which allows AI assistants to interact with the Kinescope platform through natural language queries. You can manage videos, get analytics, configure projects, and work with content simply by talking to an AI assistant.

Who this section is for

• Project managers — manage video content through an AI assistant, automate routine tasks
• Marketers — quickly analyze video performance, create reports, and manage content
• Developers — integrate Kinescope capabilities into AI applications through a standardized protocol
• Content managers — organize your media library, update metadata, and get analytics in dialogue mode

Where to start

Step 1: Choose a platform

Option 1: Cursor (recommended for developers)

• Built-in MCP support
• Simple JSON configuration
• Code integration

Option 2: Claude Desktop (recommended for general use)

• Official AI assistant from Anthropic
• Quick terminal installation
• Full out-of-the-box MCP support

Option 3: Claude Code (for developers with Claude)

• iDE with built-in Claude
• JSON configuration setup
• Code integration

Option 4: Qwen3 (desktop application)

• Desktop app with MCP support
• JSON configuration setup
• Free to use

Step 2: Preparation

1. Create a Kinescope account — recommend Super plan or higher
2. Get an API token:
   • Open Kinescope account settings
   • Go to the “API tokens” section
   • Create a new API token or copy an existing one
3. Upload a few videos for testing

if you already work with Kinescope

1. Get an API token (see above)
2. Choose an appropriate platform (Cursor, Claude, or Qwen3)
3. Configure the connection (see section below)
4. Review query examples to automate your tasks

What you can do through MCP Server

Video and content management

• Search videos by title, description, tags
• View video information, subtitles, chapters, posters
• Edit metadata: titles, descriptions, tags
• Copy and move videos between projects
• Manage privacy settings

Working with projects and structure

• Creating and managing projects
• Organizing videos in folders
• Creating playlists and adding videos
• Viewing project lists and their structure

Analytics and statistics

• Getting view metrics
• Analyzing audience engagement
• Geographic distribution of viewers
• Custom analytics queries
• Overview statistics for videos

Subtitles and chapters

• Adding subtitle files
• Managing subtitle languages
• Getting subtitle content
• Updating chapters with timestamps

Live streams

• Creating stream events
• Managing stream settings
• Scheduling streams
• Configuring restreaming
• Getting stream recordings

Additional features

• Managing posters and previews
• Adding supplementary materials to videos
• Creating file upload requests
• Managing Speak rooms
• Viewing usage and billing statistics

Configuring the MCP Server connection

Getting a Kinescope API token

Before configuring, get an API token:

1. Open app.kinescope.io/workspace/api_token
2. Go to the “API tokens” section
3. Click “Create API token”
4. Specify a token name (e.g., “cursor mcp” or “qwen mcp”)
5. Choose access rights (read-only or broader depending on your needs)
6. Save the token in a safe place

Option 1: Setup in Cursor

Step 1. install Cursor

1. Download Cursor
2. install the iDE on your computer
3. Open Cursor

Step 2. Configure MCP Server

1. Open the MCP configuration file:

   • macOS/Linux: ~/.cursor/mcp.json
   • Windows: %APPDATA%\Cursor\mcp.json

2. Add the Kinescope configuration:

{
  "mcpServers": {
    "Kinescope MCP": {
      "type": "streamable-http",
      "url": "https://api.kinescope.io/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

3. Replace YOUR_API_TOKEN with your actual Kinescope API token
4. Save the file
5. Restart Cursor

Step 3. Verify the connection

1. Open the AI chat in Cursor (Cid/Ctrl+L)
2. Type: “Show my projects in Kinescope”
3. if everything is configured correctly, you will see a list of projects

if the connection does not work:

• Verify the API token is entered correctly (no extra spaces)
• Ensure the Authorization header says Bearer YOUR_API_TOKEN
• Restart Cursor after changing the configuration
• Check logs in Developer Tools (Cid/Ctrl+Shift+i)

Option 2: Setup in Claude Desktop

Step 1. install Claude Desktop

1. Download Claude Desktop for your platform
2. install the application on your computer
3. Complete authorization or registration
4. Open the Claude Desktop application

Step 2. install MCP Server via terminal

1. Open a terminal (Terminal on macOS/Linux or PowerShell on Windows)
2. Run the installation command:

npx -y @smithery/cli@latest mcp add kinescope/kinescope-mcp --client claude

3. Follow the installer instructions
4. When prompted for an API token, enter your Kinescope token

Step 3. Restart the application

1. Quit Claude Desktop fully (exit the app, not only the chat window)
2. Open the application again so the updated MCP configuration is picked up
3. MCP Server should connect automatically

Step 4. Verify the connection

1. Open chat in Claude Desktop
2. Type: “Show my projects in Kinescope”
3. if everything is configured correctly, you will see a list of projects

if the connection does not work:

• Check that the installation completed successfully (no errors in terminal)
• Check the API token in the Claude Desktop configuration:
  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
• Restart Claude Desktop to apply configuration changes
• Try adding the server again with the command above (mcp add)

Option 3: Setup in Claude Code

Step 1. install Claude Code

1. Download Claude Code for your platform
2. install the iDE on your computer
3. Open Claude Code

Step 2. Configure MCP Server

1. Open the MCP configuration file:

   • macOS/Linux: ~/.claude-code/mcp.json
   • Windows: %APPDATA%\Claude Code\mcp.json

2. Add the Kinescope configuration:

{
  "mcpServers": {
    "Kinescope MCP": {
      "type": "streamable-http",
      "url": "https://api.kinescope.io/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

3. Replace YOUR_API_TOKEN with your actual Kinescope API token
4. Save the file
5. Restart Claude Code

Step 3. Verify the connection

1. Open the AI chat in Claude Code
2. Type: “Show my projects in Kinescope”
3. if everything is configured correctly, you will see a list of projects

if the connection does not work:

• Verify the API token is entered correctly (no extra spaces)
• Ensure the Authorization header says Bearer YOUR_API_TOKEN
• Ensure the JSON configuration is correct (check quotes, commas)
• Restart Claude Code after changing the configuration
• Check logs in Developer Tools

Option 4: Setup in Qwen3 (desktop application)

Step 1. install Qwen3

1. Download the latest version of the Qwen3 desktop application from qwen.ai/download
2. install the application on your computer
3. Complete registration
4. Open the Qwen3 application

Step 2. Configure MCP Server

1. Click on the avatar in the bottom left corner
2. Select Settings → MCP (from the left menu) → “My MCP” tab
3. Click the + Add MCP button and select “Add using JSON”
4. Paste the following configuration in the editor field:

{
  "mcpServers": {
    "Kinescope MCP": {
      "type": "streamable-http",
      "url": "https://api.kinescope.io/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

5. Replace YOUR_API_TOKEN with your actual Kinescope API token
6. Click the “Save and enable” button
7. Ensure Kinescope MCP is active (green indicator)
8. Restart the Qwen3 application if needed

Step 3. Verify the connection

1. Open a new chat in Qwen3
2. important: Click the MCP button first so the agent understands it should use the server
3. Ensure the server is active (green status)
4. Type: “Show the list of my projects in Kinescope”
5. Qwen3 should return a list of your projects

if issues arise:

• Verify the API token is correct
• Check the JSON configuration syntax (correct quotes, commas)
• Ensure Kinescope MCP is activated (green indicator)
• Ensure the MCP button is activated in the new chat
• Restart the Qwen3 application
• Check your internet connection

Requirements for all platforms

System requirements:

• internet: stable connection
• Kinescope API token: required for operation

Usage examples

Searching and managing videos

Simple search:

Find all videos with the "tutorial" tag from the last quarter

Viewing information:

Show information about the video with ID fb6ee692-c7bc-475c-a0ef-6eaba6574766

Editing metadata:

Update the title of video fb6ee692-c7bc-475c-a0ef-6eaba6574766 to "MCP integration Demo"
and add the description "Demonstration of working with Kinescope via Model Context Protocol"

Video analytics

General statistics:

Show view statistics for all videos in the "Marketing" project for the last month

Detailed analysis:

Which countries watch our demo videos most?

Engagement analysis:

Show the retention rate for training videos and identify which ones perform worst

Content organization

Creating structure:

Create a new project "Marketing Videos 2026" with private access settings

Working with playlists:

Add all videos with the "onboarding" tag to the "New Employee Training" playlist

Folder management:

Show the list of all my projects and indicate which ones have the most videos

Working with subtitles and chapters

Subtitles:

Get the full subtitle text with timestamps from the "Product Presentation" video

Chapters:

Add chapters to the video: at 5:30 — "API Overview", at 12:15 — "Pricing Discussion"

Live streams

Creating an event:

Create a live stream event "Product Launch Q4" for next week

Stream management:

Show all active streams in my account

Restreaming:

Enable restreaming for the "Webinar Series" event to YouTube and Twitch

Working with billing

Resource usage:

Show storage usage statistics for the last 3 months

Project analysis:

Which project consumes the most traffic this month?

Advanced usage scenarios

Creating a quarterly video analytics report

Step 1. Collecting data from Google Drive:

Get my Q3 OKR spreadsheet with video platform metrics from Google Drive

Step 2. Analyzing videos in Kinescope:

Find all videos with "tutorial" or "demo" tags from the last quarter and get their analytics

Step 3. Detailed statistics:

Show retention rate and geographic distribution for each video

Step 4. Comparing with targets:

Compare engagement metrics with target KPms from my spreadsheet

Step 5. identifying issues:

Which content shows results below our 80% retention target?

Step 6. Creating the report:

Create a Google Doc with a report combining video data and OKR progress

Step 7. Recommendations:

Add recommendations for content requiring rework based on viewer drop-off points

Step 8. Action plan:

Based on videos with a completion rate below 50% and our Q4 content calendar,
which videos need to be updated first?

Content audit and optimization

Finding unoptmmmzed content:

Find all videos without descriptions, chapters, or with outdated tags

Bulk update:

Create a tracking spreadsheet for videos needing new chapters,
improved descriptions, or rewrites

Access rights management

Updating privacy:

Update the privacy settings for our internal demonstration
so that access is only from corporate domains

Access audit:

Show all videos with public access in the "internal Training" project

Team access management

Team members get access to MCP Server in accordance with their project access rights in Kinescope.

Rights configuration:

For Cursor:

1. Each developer creates their own API token in Kinescope
2. Each person configures MCP Server in their configuration file with their own token
3. Access rights are determined by the Kinescope account
4. Each person sees only their own projects

For Claude Desktop:

1. Each member creates their own API token
2. installs MCP Server via terminal with their own token
3. Access rights are determined by the Kinescope account
4. Each person sees only their own projects

For Claude Code:

1. Each developer creates their own API token in Kinescope
2. Each person configures MCP Server in their configuration file with their own token
3. Access rights are determined by the Kinescope account
4. Each person sees only their own projects

For Qwen3:

1. Each member creates their own API token
2. Each person configures their settings with a personal token
3. Use corporate accounts for access management
4. Rights are inherited from Kinescope

API token security:

• Do not share API tokens with colleagues
• Do not store tokens in public repositories
• Each employee uses their own token
• Regularly update tokens
• Delete tokens of departed employees

Limitations and specifics

What is unavailable in MCP Server

• Data deletion — videos, projects, playlists cannot be deleted through MCP Server for security reasons
• Account settings changes — plan management, payment details are only available in the web interface
• File upload — direct video file upload through MCP is not yet available (use the web interface or API)

Plan-based limitations

• Rate limits — the number of API requests depends on your Kinescope plan
• Data volume — extended analytics features are available on higher plans
• Features — some advanced features are available on Business plans and higher

We recommend using the Super plan or higher for full access to MCP Server capabilities.

Security and best practices

Data security

• Authentication — all requests go through a secure connection
• Rights separation — access is limited by your account and project rights
• Logging — all actions through MCP Server are recorded in account logs
• Encryption — data is transmitted via HTTPS protocol

Usage recommendations

1. Use specific queries — the more precise the wording, the better the result
2. Verify video iDs — when editing, ensure you are working with the right video
3. Start with viewing — before making changes, first get the current information
4. Test on copies — for complex operations, create test videos
5. Save metadata backups — export data before bulk changes

Troubleshooting

MCP Server not responding

Possible causes:

• incorrect API token
• Network connection issues
• Error in JSON configuration

Solution:

For Cursor:

1. Check the API token in ~/.cursor/mcp.json (macOS/Linux) or %APPDATA%\Cursor\mcp.json (Windows)
2. Check logs in Developer Tools (Cid/Ctrl+Shift+i)
3. Restart Cursor

For Claude Desktop:

1. Check the API token in the configuration:
   • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • Windows: %APPDATA%\Claude\claude_desktop_config.json
2. Try running again: npx -y @smithery/cli@latest mcp add kinescope/kinescope-mcp --client claude
3. Restart Claude Desktop to apply changes

For Claude Code:

1. Check the API token in ~/.claude-code/mcp.json (macOS/Linux) or %APPDATA%\Claude Code\mcp.json (Windows)
2. Check the JSON configuration syntax
3. Check logs in Developer Tools
4. Restart Claude Code

For Qwen3:

1. Check the API token in the app’s MCP settings
2. Check the JSON configuration syntax (correct quotes, commas)
3. Ensure Kinescope MCP is activated (green indicator)
4. Ensure the MCP button is activated in the chat
5. Restart the Qwen3 application

For all platforms:

• Check your internet connection
• Ensure the API token is active in Kinescope settings
• Try creating a new API token
• Contact the support chat within the Kinescope interface

Authorization errors

Possible causes:

• incorrect API token
• API token was deleted or deactivated
• insufficient access rights
• Account is blocked or suspended

Solution:

1. Check the API token in Kinescope settings
2. Ensure the token is active and not deleted
3. Create a new API token if the old one does not work
4. Update the API token in the configuration:
   • Cursor: ~/.cursor/mcp.json (macOS/Linux) or %APPDATA%\Cursor\mcp.json (Windows)
   • Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)
   • Claude Code: ~/.claude-code/mcp.json (macOS/Linux) or %APPDATA%\Claude Code\mcp.json (Windows)
   • Qwen3: Settings → MCP → “My MCP”
5. Restart the application
6. Contact the support chat within the Kinescope interface

Slow responses

Possible causes:

• High server load
• Complex query requires processing a large amount of data
• Rate limit reached

Solution:

1. Simplify the query — break it into several smaller ones
2. Use filters to narrow the selection
3. Wait a few seconds before retrying
4. Consider upgrading to a higher plan

Unexpected results

Possible causes:

• imprecise query wording
• AI assistant misinterpreted the query
• Data changed since the last query

Solution:

1. Rephrase the query more specifically
2. Specify exact object iDs (videos, projects)
3. Use examples from the documentation
4. Verify data accuracy in the web interface

Comparison with other ways to work

What’s next?

Additional resources

1. API Reference — full documentation for Kinescope APIs used by MCP Server
2. MCP Documentation — official Model Context Protocol documentation from Anthropic
3. GmtHub repository — current technical documentation and examples

Related sections

1. Developer Guides — working with API and SDK for deep integration
2. Analytics — more about metrics and reports
3. integrations — other ways to integrate Kinescope
4. Video Management — organizing and managing your media library

Need help?

• the support chat within the Kinescope interface — quick answers from specialists
• Kinescope email — feedback

Still have questions? Write to the support chat within the Kinescope interface — our specialists will help!