This MCP server implementation provides a bridge to Meilisearch, a powerful open-source search engine. It enables AI assistants to perform advanced search operations, manage indexes and documents, and configure search settings through a standardized interface. The server integrates closely with Meilisearch's API, offering features like faceted search, custom ranking, and asynchronous task management, making it ideal for applications requiring fast, relevant, and customizable search functionality.
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Create a new index.
Get information about an index.
List all indexes.
Update an index.
Delete an index.
Add documents to an index.
Get a document by ID.
Get multiple documents.
Update documents.
Delete a document by ID.
Delete multiple documents.
Delete all documents in an index.
Search for documents.
Perform multiple searches in a single request.
Get index settings.
Update index settings.
Reset index settings to default.
List tasks with optional filtering.
Get information about a specific task.
Cancel tasks based on provided filters.
Wait for a specific task to complete.
Check the health status of the Meilisearch server.
Get version information.
Get system information.
Get statistics about indexes.
Enable vector search.
Get experimental features status.
Configure embedders.
Get embedders configuration.
Reset embedders configuration.
Perform vector search.
