Best MCP servers for data analysis
Data analysis with an AI agent comes down to one thing: giving the model safe, read access to where your numbers actually live, then letting it write and run the queries. That might be a product-analytics platform, a columnar warehouse built for aggregations over billions of rows, or a transactional Postgres database you query directly. The servers below cover each of those shapes. The recurring theme is read-only access so an agent can explore freely without write risk, plus enough schema awareness that it composes correct SQL instead of guessing at column names. These are the servers we recommend for turning a question into an answer backed by your real data, each with a verified, current install config.
PostHog
PostHog
PostHog's official MCP server: query product analytics, manage feature flags and experiments, run HogQL, and triage errors from your editor.
PostHog's official server answers product-analytics questions in plain language and runs ad-hoc HogQL, so an agent can pull funnels, retention, and event trends without you opening the dashboard.
ClickHouse
ClickHouse
ClickHouse's official MCP server lets agents list databases and tables and run read-only SQL against a ClickHouse cluster.
ClickHouse's official server gives read-only SQL over a cluster built for fast aggregations across billions of rows, ideal when analysis means scanning large event or time-series tables.
DBHub (Postgres)
Bytebase
A universal database MCP gateway that connects agents to Postgres (and others) via a DSN.
DBHub points an agent at any Postgres database via a DSN, exploring schema progressively and running transaction-aware SQL so it queries your operational data accurately.
Neon
Neon
Neon's official MCP server lets agents create projects and branches, run SQL, and drive safe schema migrations on serverless Postgres.
Neon's official server is the pick when your analytics tables live on serverless Postgres: the agent runs SQL and can branch the database to test heavy queries against a copy.