The no-code path is short: use an assistant that supports remote MCP connectors, add a connector that can search video, sign in, then ask for what you want in plain language. Adding a connector is a login and a menu, not a build. Code only enters the picture if you decide to build the searchable index yourself, which is a separate project with a separate budget.
Why the assistant cannot just watch the file
On its own, an AI assistant reads text. A video file is opaque to it until something has turned the picture and the sound into something searchable, and that work happens before your question, not during it. This is the part that surprises people who expect to drop a folder into a chat and start asking. What indexing does to a video, and why it has to happen first, is covered in the step that runs before any search does.
The routes, sorted by whether a developer is involved
Pasting clips into the conversation needs no code and no setup. It also needs you to know which file to paste, which is the problem you were trying to solve.
A filesystem connector needs no code either. It gives the assistant your file names, folders, and dates, and stops there. Whether an assistant can open what you point it at, and what it sees when it does, is the whole question in what an assistant can actually read from your library.
Building your own index is the route where code lives. Transcription, chunking, embeddings, a vector store, then a tool the assistant can call. Cloud transcription and indexing services shorten it, but somebody still writes and maintains the glue, and the result stops at speech unless you add a second pipeline for what is on screen.
A hosted video retrieval connector is the fourth route and the one that matches the question. The service has already done the indexing, and the assistant reaches it over a standard remote MCP address with an account login.
Ask for a moment in your own footage from an AI chat
Vivu works this way with any assistant that supports remote MCP, Claude and ChatGPT included, using the same address and the same Vivu account. Videos go into a Vivu project first and are indexed there once, and that index is what later questions read from. There are two search modes, and they answer different questions: a fast pass tells you which videos are probably relevant, while a precise pass runs as a job and comes back with short ranges plus a line of reasoning for each. The fast pass is the one that hands back whole videos rather than moments, so if your clips are short you often end up dragging the playhead anyway, and the precise pass is what narrows a query about a screen or a phrase down to the seconds where it appears. Precise takes longer and spends more of your search allowance, so fast first and precise once you know the footage is there is the habit worth forming. The ranges you keep export as original clips.
When you do not need any of this
If you have one video and you know roughly where the moment is, scrubbing wins. If your library is organised well enough that file names answer your questions, keep the naming convention and spend nothing. If the thing you actually want is a transcript to read, transcription alone is a smaller purchase than a retrieval layer, and it will answer questions about what was said.
Where the no-code route stops
Searches run inside one project at a time, so you plan around projects rather than one giant library. Footage has to be uploaded and indexed before it can be searched, which is real time and a real decision about what is worth ingesting. Search consumes an allowance, and the free and paid tiers are listed on Vivu's pricing page. Results are ranges you open and preview rather than frame-exact points, so anything heading into an edit gets trimmed by hand. And what comes back still needs a person to look at it, which is a habit worth building early, along with a clean way to pass the selected ranges to an editor.
If your question is "where in my footage did that happen", the connector route answers it without a line of code. If your question is "how do I control exactly how matching works", you are describing the build, and you will need the developer after all.
FAQ
Do I need a developer to add an MCP connector?
No. A remote MCP connector is added by pasting an address into your assistant's connector settings and signing in, the same shape as authorising any web app. The work a developer would do sits on the other side of that address, in the service that indexed your video.
Why did my search return whole videos instead of a specific moment?
That is usually the fast search mode doing what it is designed to do, which is tell you which videos are likely relevant rather than where in them the moment sits. On short clips the result can look like a list of files. Running the same query in the precise mode is what narrows it to the seconds you can actually use.
Can I search video I have not uploaded anywhere?
Not with this kind of connector. Searching by content requires an index, and an index requires the service to have processed the video, which means uploading it first. Tools that work on files sitting on your own disk without uploading them are reading file names, not contents.
What should I type into the chat?
Describe the moment the way you would describe it to a colleague, including what is visible and what is being said. Something like find the part where the presenter explains why they changed the pricing works better than a keyword. Short, literal descriptions tend to come back with tighter ranges than long ones with several conditions stacked together.