Enables AI assistants to enhance their responses with relevant documentation through a semantic vector search, offering tools for managing and processing documentation efficiently.
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Highlight AISearch through the documentation using vector search. Returns relevant chunks of documentation with source information.
List all available documentation sources. Provides metadata about each source.
Extract URLs from text and check if they're already in the documentation. Useful for preventing duplicate documentation.
Remove documentation from a specific source. Cleans up outdated or irrelevant documentation.
List all items in the processing queue. Shows status of pending documentation processing.
Process all items in the queue. Automatically adds new documentation to the vector store.
Clear all items from the processing queue. Useful for resetting the system.
Add new documentation directly to the system by providing a URL. Automatically fetches, processes, and indexes the content. Required parameter: `url` (must include protocol, e.g., https://).
Index a local code repository for documentation. Required parameter: `path` (absolute path to repository).
List all indexed repositories with their configurations. Shows include/exclude patterns and watch status.
Re-index a repository with updated configuration. Required parameter: `name` (repository name).
Remove a repository from the index. Required parameter: `name` (repository name).
Start or stop watching a repository for changes. Required parameters: `name` (repository name) and `action` ('start' or 'stop').
Get the current status of repository indexing operations. Optional parameter: `name` (repository name) - if not provided, returns status for all repositories.
