Meilisearch MCP

The Meilisearch MCP server exposes an entire Meilisearch instance to an AI client as callable tools, so an assistant can build and debug a search setup without the developer writing HTTP calls. Index tools create, list and delete indexes and report index metrics. Document tools retrieve entries with pagination and add or update documents. The search tool queries a single index or several at once with filtering and sorting. Settings tools read and update ranking rules, faceting and the rest of the index configuration, which is the part of Meilisearch most people iterate on when relevance is off. Operational coverage goes further than the basics. API key tools list, create and delete keys, so an agent can mint a scoped search key for a frontend. Task tools read a single task or the task queue and cancel or delete tasks, which matters because indexing in Meilisearch is asynchronous and failures surface as task records. Health check, version and stats tools report whether the instance is up, what it runs and how large each index has grown. Connection tools show and change the target instance URL and key at runtime, so one server can move between a local instance and a hosted one. The server is a Python package installed with pip or uvx and pointed at an instance through the HTTP address and master key environment variables. It suits developers wiring up search, and teams who want an assistant to inspect a failing index rather than reading raw API responses.