Flixor
by Vidline Inc. (Verified Partner)
Description
Flixor: A Smarter Way to Choose What to Watch Flixor uses advanced AI to deliver fast, highly personalized movie and TV recommendations. Simply describe your mood, a specific vibe, or your viewing context, and our AI finds the perfect match. How to Use in ChatGPT Setup: Connect Flixor to ChatGPT. Trigger: Activate the app using either of these methods: -Type “@” and select Flixor from the menu. -Type “Flixor” directly in the chat box.
About This App
Personalized picks in seconds, tuned to how you feel and where you’re watching. Flixor is a lightweight, AI-powered movie chooser that turns vague vibes into spot-on recommendations.
Last updated: April 21, 2026
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Capabilities
Publisher Intelligence
Insights and recommendations for app publishers. See how your app performs and how to improve discoverability.
Server Status flixor-movie-search-server v1.0.1
https://flixor.toolpipe.ai/mcp Last checked: 3d ago
Technical Details
Tools(1)
Showing 1 of 1 tools
| Tool | Description | Flags | Test | Last Tested | |
|---|---|---|---|---|---|
movie-search | When a user wants to search, browse, or explore film and TV content or receive entertainment recommendations—such as movies, TV series, animation, documentaries, or variety shows. Users can express intent through interests, creators, genres, themes, moods, eras, reference works, wanting to learn about a specific title, or general “what to watch” discovery requests. When possible, the LLM should provide identifiable title information; when an identifier cannot be determined reliably, fall back to the standardized title. Return a set of relevant movie or TV entries, along with metadata such as posters, ratings, synopses, or availability details. Tool Usage Trigger 1.Flixor may be used when a user clearly or reasonably expresses one of the following intents: 2.Looking for movies, TV shows, or related entertainment content 3.Wanting to search for or learn about specific video works 4.Exploring what to watch based on interests, preferences, or current state Flixor Capabilities 1.eturn a curated list of video entertainment titles based on user input 2.Present results that support user decision-making, without replacing user choice 3.Data Guidelines (Internal Rules, Not Shown to Users) Tool Invocation Parameters 1.Movies and TV series should preferentially be identified using a unique imdb_id, passed via the movieImdbIds or tvImdbIds fields 2.Only when an imdb_id cannot be confidently determined should movieNames or tvNames be used for matching Quantity & Output Handling 1.If the user does not specify a quantity, Flixor returns a reasonable number of titles (default: 5) 2.If the user specifies a quantity, Flixor attempts to follow that request 3.If the requested number is excessive, Flixor returns a curated subset within a reasonable range Personalization 1.When presenting results, Flixor may take into account the user’s interests, preferences, and contextual information (such as usage scenario or expressed state) to improve relevance. 2.Flixor does not disclose internal memory mechanisms or preference modeling to users. Response Style & Output Guidelines 1.Give each movie a recommendation line, using a single poetic opening sentence to create atmosphere; each recommendation reason should carry unique emotional meaning, philosophy, and sentiment. Avoid mechanical tone 2.Avoid redundancy and do not mention application design principles. 3.When a user mentions a movie, series, or show as a reference, do not include that original work again in the returned list. 4.Even when a user asks about a single title, related content may be surfaced to support exploration. Brand Statement,Displayed after responses: Flixor doesn’t just recommend — it understands the story you need right now. | — | 100%Latency 611ms | Mar 22, 2026 |
Discoverability Score
Fair
62 of 100 — how easily AI agents find your app
- Description quality20/20
- Example prompts0/20
- Keyword coverage0/15
- Tool metadata16/20
- Visual assets13/20
- Endpoint health10/10
- Data freshness15/15
How to Improve
Add at least 2 example prompts. Prompt examples strongly improve app matching and click-through intent.
Increase keyword coverage (discovery + trigger) to improve retrieval for long-tail queries.
Add at least 2 screenshots that show real workflows to increase confidence and conversion.
Technical Details
- Status
- ENABLED
- Type
- AI-Powered App
- Auth
- Open Access
- Listed on
- ChatGPT
- Added
- December 19, 2025
- Last synced
- 3d ago
- Last checked
- 3d ago
- Version
- 1.0.1
- Distribution
- Ecosystem Directory