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Explorer/MCP/registry/io.twelvelabs/twelvelabs-mcp-server
✓ REGISTRY VERIFIEDREMOTE◉ LIVE SCAN

io.twelvelabs/twelvelabs-mcp-server

registry/io.twelvelabs/twelvelabs-mcp-server

TwelveLabs MCP: video indexing, search, analysis, and embeddings for AI applications.

19 tools available
The Journeyman with a Quirk
Some history here. A few things flagged; nothing serious, but we wanted you to know.
Time indexed (5mo)
19toolsRemote/ HTTP5moindexed1signal
Checked Sep 16, 2026
Quality Score
32/95
Emerging
Risk Score
6/100
Low
How is this calculated?
Quality Breakdown
Tenure13.7/20
151 days indexed
Capability18.6/25
Tools: 6.6/13 (19 tools)
Description: 5/5
Endpoint: 7/7
Adoption0/25
Use count: 0/20 (0 uses)
Multi-registry: 0/5 (1 registry)
Reliability0/25
Currently live: 0/10
Uptime history: 0/15 No checks yet
Security scan: 0 pts in v1.0; ready to weight when coverage improves
Incomplete Data Cap (60)
Usage data is not available for this server. Quality is capped until adoption can be measured.
Risk
6Low
See Security Signals section for details.
The scanner shows
19 tools. Registry verified. A few things worth knowing about. Check the details below.
First indexed Apr 18, 2026
Security Signals1 rule group · 1 finding
No authentication requiredHigh
Server responded without authentication
Server Profile
Tools catalogued
19
19 tools available. Full list below.
Hosting
Remote / HTTP
Runs on the internet. No access to your filesystem, SSH keys, or environment variables.
Registry presence
Verified
Listed on the Official MCP Registry under Linux Foundation governance.
Liveness
No liveness checks recorded yet.
Publisher Verification
✓ Listed on the Official MCP Registry under Linux Foundation governance.
Published version: 1.0.1
Connect to this server — endpoint 1
STREAMABLE-HTTP
https://mcp.twelvelabs.io
Headers (1)
X-api-keyREQUIRED🔒 SECRET
Twelvelabs API key for authentication
Connect to this server — endpoint 2
SSE
https://mcp.twelvelabs.io/mcp
Headers (1)
X-api-keyREQUIRED🔒 SECRET
Twelvelabs API key for authentication
Tools (19)We asked this server directly for its tool list on Apr 19.
create-index
Create a new twelvelabs video index. An index is a basic unit for organizing and storing video data consisting of video embeddings and metadata. Indexes facilitate information retrieval and processing. If you plan to use search or video embedding, you should use the embedding model. If you plan to analyse videos to generate summaries, chapters, highlights, etc., you should use the generative model. If you don't provide a model, we will use both models by default.
list-indexes
List all twelvelabs video indexes.
delete-index
Delete a twelvelabs video index
get-sample-videos
Get sample videos (name, description, url and duration in seconds). This tool will return a list of sample videos that can be used to test the twelvelabs platform (video indexing & embedding, search, analysis, etc.). You should use this tool if the user doesn't have a video url to index. You can offer the user to select a video from the list.
start-video-indexing-task
Start a twelvelabs video indexing task. This will allow the video to be used by the embedding model and searched in natural language. If no indexId is provided, we will add the video to the default index. You can provide either a videoUrl (for remote videos), a videoFilePath (for local video files), or a folderFilePath (to index all videos in a local folder). If both videoUrl and videoFilePath are provided, we will use the videoUrl. Supports Google Drive links (file or folder). For Google Drive folders, all MP4 videos will be indexed and multiple tasks will be started. You can also pass optional userMetadata as a JSON string of key-value pairs to attach metadata to the indexed video(s).
get-video-indexing-tasks
Get details about video indexing tasks. If you provide a taskId, we will return details (including the status) of that task. If not we will return the details of the latest 10 indexing tasks that were created. Possible statuses are: - Validating: Your video has finished uploading, and the API service is validating it by ensuring it meets the requirements listed on the Create a video indexing task page. - Pending: The platform is spawning a new worker server to process your video. - Queued: A worker server has been assigned, and the platform is preparing to begin indexing. - Indexing: The platform transforms the video you uploaded into embeddings. An embedding is a compressed version of the video and contains all the information that TwelveLabs’ deep-learning models need to perform downstream tasks. - Ready - Failed
Show all 19 tools ↓
list-videos
List all videos in a twelvelabs video index. If you don't provide an indexId, we will use the default index. This tool will return for each video of the index: - the videoId: needed for video analysis. - the original video filename (if there is one). Use this tool if you don't know the videoId of the video the user wants to analyse, you can display the different filenames and ask the user to select the video they want to analyse.
search
Search in twelvelabs videos using natural language descriptions. The twelvelabs platform interprets your query to find matching content based on visual elements, actions, sounds, and on-screen text. The search is performed on all videos in the index (or the default index if no index is provided). It will return the start and end time of the matching segments in the video. The search results include: - Filename and videoId for each matching video - user_metadata (if any was attached during indexing) - Thumbnail URLs for each segment (pre-signed S3 URLs, valid for 1 hour) - Start/end times and relevance rank for each segment For each video that has matching segments, you should display: - Filename of the video - user_metadata key-value pairs - A table of segments with rank, timecode, and a clickable hyperlink for the thumbnail (do NOT use markdown image syntax, use a text hyperlink like [View thumbnail](url) instead). Supports three search modes: - Text only: provide just a query string - Image only: provide queryMediaUrl or queryMediaFile with queryMediaType "image" - Composed (text + image): provide both query and an image (via URL or file path) for refined results (e.g. image of a car + "red color"). Requires Marengo 3.0. For entity search, include the entity ID in the query using the format: "<@entity_id> action description"
create-entity-collection
Create a new entity collection. Entity collections group related entities (people or objects) for entity search. For example, create a collection per sports team or film cast. Requires Marengo 3.0.
list-entity-collections
List all entity collections. Entity collections contain entities (people/objects) used for entity search.
delete-entity-collection
Delete an entity collection and all its entities.
create-asset
Upload a reference image as an asset. Assets are used as reference images when creating entities for entity search. Provide either a publicly accessible image URL or an absolute path to a local image file. Use multiple reference images per entity for better accuracy across different angles and lighting.
create-entity
Create an entity within a collection. An entity represents a specific person or object you want to find in videos. You must provide at least one asset ID (reference image). Multiple reference images improve accuracy. After creating an entity, search for it using: <@entity_id> action description
list-entities
List all entities in an entity collection.
delete-entity
Delete an entity from a collection.
start-video-embeddings-task
Start a new twelvelabs video embeddings task that uploads a video to the platform and creates one or multiple video embeddings.
get-video-embeddings-tasks
Get details about video embeddings tasks. If you provide a taskId, we will return details (including the status) of that task. If not we will return the details of the latest 10 embeddings tasks that were created. Possible statuses are processing, ready, or failed.
retrieve-video-embeddings
Retrieves the video embeddings from a ready twelvelabs video embeddings task or from an indexed video.
analyse-video
Analyse a video with twelvelabs models. You will always need to provide a videoId to use the tool. If you don't have a videoId, you need to use the list-videos tool first and ask the user to select the video they want to analyse. Videos need to be indexed to be available for analysis, you can use the start-video-indexing-task tool to index a new video. Provide a prompt to guide the analysis. The prompt can request titles, topics, hashtags, summaries, chapters, highlights, or any open-ended analysis such as tables of content, action items, memos, and detailed analyses.

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