Best Data Analytics Plugins, Skills, and MCP Servers in 2026
Research-backed data and analytics plugins, skills, and MCP servers with platform availability and direct setup routes.
Updated July 25, 2026
These extensions let agents reach real databases, warehouses, BI platforms, and product-analytics tools, then run queries and follow repeatable analysis workflows. The main decision is how much access to grant: broad exploration is convenient, but production data usually deserves scoped, read-only credentials.
What it isThe official MongoDB package brings together the MongoDB MCP Server and reusable skills for schemas, queries, aggregations, indexes, connections, and Atlas workflows, giving an agent both live database access and current MongoDB practice.When to useThe result is an agent that inspects and works with MongoDB while grounding its code and database advice in MongoDB’s current guidance rather than generic patterns. Keep access read-only and least-privilege until a task clearly needs writes.What you needA MongoDB deployment or Atlas account to connect to.
What it isGoogle’s official, experimental local MCP server for the Google Analytics Admin and Data APIs. It exposes read-only tools to list accounts and properties, inspect custom dimensions and metrics, and run core, funnel, and realtime GA4 reports.When to useUse it to answer analytics questions - traffic, conversions, funnels, and realtime activity - directly against GA4 instead of exporting reports by hand. Access is read-only by scope, so it reports on data but cannot change GA configuration. Marketers who reach it from the Marketing & SEO guide land here, where it is ranked among data and analytics extensions.What you needA Google Cloud project with the GA APIs enabled and an account with access to the GA4 properties; the server runs locally.
What it isA local MCP gateway for PostgreSQL, MySQL, MariaDB, SQL Server, and SQLite. It deliberately exposes just two core tools, schema and object search plus SQL execution, alongside optional parameterized custom tools.When to useOne token-efficient interface covers several database engines, and the guardrails are the real draw: read-only mode, row limits, query timeouts, and TLS/SSH support. Use a dedicated least-privilege account regardless, and keep the server off untrusted networks.What you needA local gateway process plus a least-privilege account on the database it queries.
What it isAn integration that pairs Neon’s Serverless Postgres skill with the Neon MCP Server for live project and database work. The agent can provision databases, create branches, run queries and migrations, and validate connections while following current Neon patterns instead of generic Postgres advice.When to useReach for it when an agent needs to build against or manage a Neon database. Neon positions the MCP as a development and testing tool, and with write access it can perform destructive database and project operations, so favor read-only and project-scoped restrictions for casual work.What you needA Neon account and project.
What it isRedis gives agents live database access through its official MCP server plus coding guidance through official skills. The MCP covers data structures, keys, and query, search, and vector operations with read and write access; the skills carry Redis application patterns.When to useUse the MCP for operational work against a real instance and the skills for correct Redis application design. Because the server can write, connect it with tightly scoped ACL credentials and prefer read-only or narrow permissions until a task clearly needs more.What you needA Redis connection URI; scope it with a least-privilege ACL user.
What it isMicrosoft’s Power BI Modeling MCP for working with semantic models through an agent: inspecting and editing model structure, running DAX queries, and operating across PBIP, Fabric, and Power BI Desktop workflows. It ships as a Public Preview npm package that runs locally.When to useUse it for supervised semantic-model development, where DAX and model work go through structured tools instead of brittle UI automation. It is Public Preview software with write access that can modify models, so work against backups with limited permissions rather than casually against production models.What you needA Windows/local runtime and access to a Power BI model (Desktop, Fabric, or PBIP).
What it isA server framework that connects agents to a wide range of SQL, NoSQL, analytics, and cloud databases. It can expose ready-made exploration tools for quick work, or narrowly defined production queries where you control exactly which operations an agent can invoke.When to useThe same server works across Claude, Codex, Cursor, and custom frameworks, handling connections, pooling, auth, and observability in one place. The trade-off worth respecting: prebuilt SQL tools are broad and convenient, but sensitive production data should stay behind read-only accounts and scoped, purpose-built tools.What you needA local Toolbox server plus connection credentials for the databases you point it at.
What it isGoogle’s warehouse offered through three routes: a managed remote MCP endpoint, a managed Claude connector, and a local path via MCP Toolbox for Databases. Agents can discover datasets and tables, inspect metadata, and run SQL.When to useAccess runs through existing Google Cloud OAuth, IAM, audit, and billing controls, so data stays inside current governance. Prefer the read-only SQL tool. The managed endpoint caps queries at three minutes and 3,000 returned rows and skips Drive external tables, so large pulls need another path.What you needA Google Cloud account - access runs through your existing IAM, audit, and billing.
What it isAn official integration that combines a hosted MCP connection with more than 30 skills covering product analytics, feature flags, experiments, error tracking, surveys, dashboards, and LLM analytics.When to useIt gives an agent live product and production context, then lets it investigate trends and errors or manage PostHog workflows without switching tools. Note that the MCP can write, changing flags, experiments, dashboards, and surveys, so grant that access deliberately.What you needA PostHog account and project.
What it isAn official integration that takes two forms. The Claude and Codex plugins delegate Snowflake prompts to Cortex Code, while the Cursor plugin connects to a Snowflake-managed MCP server. Both give agents governed access plus Snowflake-specific skills.When to useThose skills cover SQL, governance, ML, dynamic tables, semantic views, cost, performance, and Cortex services, so an agent works with Snowflake instead of guessing. The two routes share the name but not the same architecture, and queries and Cortex features may consume paid compute.What you needA Snowflake account; Claude and Codex prompts route through Cortex Code.
What it isChroma’s official MCP server lets an agent create, query, update, and delete vector-database collections and documents, with vector-similarity, full-text, and metadata-filtered search. It runs self-hosted in ephemeral, persistent-local, self-hosted-HTTP, or Chroma Cloud modes.When to useReach for it when an agent needs semantic retrieval, a project knowledge base, or explicit persistent memory backed by Chroma. The default ephemeral client loses data on restart, so choose the mode deliberately, and note that collection and document tools can write and delete.What you needA local runtime for the server, or a Chroma Cloud account for the hosted mode.
What it isTableau MCP gives agents governed access to Tableau content and analytics. It comes two ways: a Tableau-managed remote MCP service for eligible Cloud or Server accounts, and an official open-source server you host yourself.When to useUse it when Tableau already holds your organization’s governed analytics and you want the agent to query it while preserving platform permissions. Prefer the managed MCP when your account SKU supports it; use the self-hosted server for self-managed or unsupported environments.What you needA Tableau Cloud or Server account; the managed route depends on account SKU and admin entitlement.
What it isAn official agent stack that pairs ClickHouse-specific skills with live, read-only access to ClickHouse Cloud through MCP. The skills carry current database knowledge; the connection lets an agent inspect real services and data.When to useInstead of generic SQL advice, an agent can design schemas, optimize queries and ingestion, troubleshoot clients, and inspect actual Cloud services, schemas, costs, and pipelines. The general Cloud MCP is read-only, so it analyzes rather than changes your data.What you needA ClickHouse Cloud account for the live, read-only connection.
What it isDuckDB Skills are the project’s official, portable agent instructions for the embedded analytical engine - nine skills covering SQL, performance, data formats, extensions, and workflows. They are guidance, deliberately not a live-database MCP.When to useUse them for local analytical work where DuckDB is already the execution engine, so an agent writes correct, performant DuckDB SQL without a hosted account. Keep them distinct from MotherDuck’s hosted MCP, which is the cloud service rather than the local engine.What you needNothing beyond your existing local DuckDB or project - the skills add no service.
What it isDatabricks connects agents to governed lakehouse data and AI assets - Unity Catalog objects, tables, functions, vector search, and Databricks apps - while also shipping an official collection of development skills. Live access runs through Databricks-managed MCP services.When to useReach for it for Databricks-centric analytics, data engineering, and AI development, where the agent should work against real catalog data without bypassing governance. Distinguish the live MCP access from the portable skills, which carry development knowledge but do not themselves grant workspace access.What you needA Databricks workspace with OAuth or a personal access token; exposed objects follow Unity Catalog permissions.
What it isAn MCP server built into each enabled Metabase instance. It lets an agent search tables and metrics, inspect fields and sample values, build and run queries, create or update Metabase content, and return interactive charts.When to useThis gives an agent governed analytics context instead of a raw database connection: results and actions stay scoped to the signed-in user’s permissions. Worth knowing that content tools can write, so the same permissions can create or change dashboards, not just read them.What you needA Metabase instance with the MCP enabled; actions stay scoped to your signed-in permissions.
What it isAn authenticated product-analytics MCP paired with vendor-authored plugins and skills for analysis, dashboards, experiments, session replay, feedback, taxonomy, and instrumentation, giving an agent governed access to Amplitude projects.When to useIt lets an agent query and edit analytics objects, investigate funnels and experiments, analyze replay and feedback, and plan instrumentation, using repeatable workflows instead of generic prompting. One limit worth remembering: the MCP is not an event-ingestion endpoint, so production events still go through the SDK or HTTP API.What you needAn Amplitude account and project.
What it isAn official toolkit that pairs vector-database tools with guided skills for semantic search, RAG, full-text search, and Pinecone Assistant. An agent can create and inspect indexes, upsert and search records, and rerank results.When to useThis is the integration to reach for when building or operating search, RAG, recommendation, or document-Q&A features on Pinecone, since the agent both follows the workflow and acts on real indexes and data. The MCP centers on integrated-index operations; the CLI and packaged scripts cover broader or batch work.What you needA Pinecone account and API key.
What it isAn official stack that combines analytics-engineering skills with the dbt MCP Server, giving an agent project, semantic-layer, CLI, job, and documentation context for work in a dbt project.When to useWith it, an agent can build and test models, use MetricFlow, troubleshoot jobs, work with Mesh, and run dbt commands using current product guidance. The skills help even without live access, though many assume an existing dbt project, and CLI/SQL tools can change models and warehouse state.What you needAn existing dbt project; job and semantic-layer routes need a dbt Cloud account.
What it isMixpanel’s official hosted MCP connects an agent to product-analytics work: queries, funnels, retention, dashboards, taxonomy, experiments, feature flags, session replays, and data quality. Claude presents it as a connector; Codex has a Mixpanel plugin.When to useReach for it when an agent needs conversational read and write access to Mixpanel product analytics. MCP access must be enabled by an organization admin, and the server can write data and is not covered for HIPAA at research time, so scope it deliberately.What you needA Mixpanel account with MCP enabled by an admin.
What it isA first-party bundle for moving from a business question and authorized data to a validated analysis, chart, dashboard, notebook, report, or recommendation. The live package currently holds 15 skills, 20 optional apps, and 3 app templates.When to useInstead of jumping straight to a confident chart, it routes work through business context, data-quality checks, KPI design, metric diagnosis, validation, and visualization. It draws on uploaded files or connected warehouses, but it cannot make weak or mismatched data trustworthy, so validate definitions, joins, and time windows first.What you needAuthorized access to the data you analyze. Currently a Codex-only bundle.
What it isLooker connects agents to governed analytics through Google’s managed MCP service, delivered as an official Claude plugin and as a Preview managed MCP endpoint for other clients. The agent works with Looker’s semantic model and analytics tools rather than a raw database.When to useUse it for organizations already standardized on Looker that want semantic-model-aware business intelligence - governed metrics and Explores - instead of raw SQL access. It requires admin enablement, and the managed MCP is a Preview service, so confirm its status before relying on it.What you needA Looker instance with the managed MCP enabled by an admin.
What it isMotherDuck’s official integration lets an agent query, prepare, visualize, and manage cloud DuckDB data - reading schemas, running SQL, working with views, and creating shareable Dives. Claude presents it as a connector; Codex has a MotherDuck plugin and app.When to useUse it when an agent should behave like an iterative analyst over MotherDuck data, moving from schema to SQL to a shareable Dive. It is the hosted cloud service rather than the local DuckDB engine, and queries and writes can change data and incur warehouse usage.What you needA MotherDuck account.
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Claude presents it as a connector; Codex has a MotherDuck plugin and app.`})]}),_jsxs(`section`,{className:`uai-itemcard-section`,children:[_jsx(_components.p,{children:_jsx(_components.strong,{children:`When to use`})}),_jsx(_components.p,{children:`Use it when an agent should behave like an iterative analyst over MotherDuck data, moving from schema to SQL to a shareable Dive. 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the broad gateway, with production-grade control over which operations an agent can run`]}),`\n`,_jsxs(`p`,{style:{margin:`0.15rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#dbhub`,children:`DBHub`}),` - the deliberately small alternative: two core tools, read-only mode, row limits`]}),`\n`,_jsx(`p`,{style:{margin:`1.5rem 0 0`,fontWeight:600},children:`Living inside one database product?`}),`\n`,_jsxs(`p`,{style:{margin:`0.35rem 0 0`},children:[`→ Official packs ground the agent in your live service - `,_jsx(`a`,{href:`#clickhouse`,children:`ClickHouse`}),`, `,_jsx(`a`,{href:`#mongodb`,children:`MongoDB`}),`, `,_jsx(`a`,{href:`#snowflake`,children:`Snowflake`}),`, `,_jsx(`a`,{href:`#bigquery`,children:`BigQuery`}),`, `,_jsx(`a`,{href:`#redis`,children:`Redis`}),`, `,_jsx(`a`,{href:`#neon`,children:`Neon`})]}),`\n`,_jsxs(`p`,{style:{margin:`0.15rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#pinecone`,children:`Pinecone`}),` or `,_jsx(`a`,{href:`#chroma`,children:`Chroma`}),` when the job is vector search, RAG, or memory`]}),`\n`,_jsx(`p`,{style:{margin:`0.35rem 0 0`,fontSize:`0.9rem`,color:`#71717a`},children:`Prefer the vendor pack over a generic gateway when you are on that product.`}),`\n`,_jsx(`p`,{style:{margin:`1.5rem 0 0`,fontWeight:600},children:`Analytical SQL - local engine or cloud warehouse?`}),`\n`,_jsxs(`p`,{style:{margin:`0.35rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#duckdb`,children:`DuckDB`}),` - official skills for the embedded engine, no account needed`]}),`\n`,_jsxs(`p`,{style:{margin:`0.15rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#motherduck`,children:`MotherDuck`}),` - the hosted cloud version, with shareable Dives`]}),`\n`,_jsx(`p`,{style:{margin:`1.5rem 0 0`,fontWeight:600},children:`Product analytics questions to answer?`}),`\n`,_jsxs(`p`,{style:{margin:`0.35rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#posthog`,children:`PostHog`}),` - analytics plus flags, experiments, and error tracking in one surface`]}),`\n`,_jsxs(`p`,{style:{margin:`0.15rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#amplitude`,children:`Amplitude`}),` - funnels, experiments, session replay, and taxonomy work`]}),`\n`,_jsxs(`p`,{style:{margin:`0.15rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#mixpanel`,children:`Mixpanel`}),` - funnels, retention, taxonomy, and experiments through a hosted MCP`]}),`\n`,_jsx(`p`,{style:{margin:`1.5rem 0 0`,fontWeight:600},children:`Governed dashboards and semantic models?`}),`\n`,_jsxs(`p`,{style:{margin:`0.35rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#metabase`,children:`Metabase`}),` - governed BI over your warehouse, scoped to each user’s permissions`]}),`\n`,_jsxs(`p`,{style:{margin:`0.15rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#looker`,children:`Looker`}),` - semantic-model-aware BI on the Google-managed service`]}),`\n`,_jsxs(`p`,{style:{margin:`0.15rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#power-bi`,children:`Power BI`}),` - supervised DAX and semantic-model development (Public Preview)`]}),`\n`,_jsxs(`p`,{style:{margin:`0.15rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#tableau`,children:`Tableau`}),` - governed Tableau content through a managed or self-hosted MCP`]}),`\n`,_jsx(`p`,{style:{margin:`1.5rem 0 0`,fontWeight:600},children:`Web and marketing analytics?`}),`\n`,_jsxs(`p`,{style:{margin:`0.35rem 0 0`},children:[`→ `,_jsx(`a`,{href:`#google-analytics`,children:`Google Analytics`}),` - read-only GA4 traffic, conversion, and funnel reporting`]}),`\n`,_jsxs(`p`,{style:{margin:`0.35rem 0 0`,fontSize:`0.9rem`,color:`#71717a`},children:[`Arriving from `,_jsx(_components.a,{href:`/plugins/marketing-seo`,children:`Marketing \u0026 SEO`}),`? 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MongoDB
Google Analytics
DBHub
Neon
Redis
Power BI
MCP Toolbox for Databases
BigQuery
PostHog
Snowflake
Chroma
Tableau
ClickHouse
DuckDB
Databricks
Metabase
Amplitude
Pinecone
dbt
Mixpanel
OpenAI Data Analytics
Looker
MotherDuck
MCP
Skill
