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Improvado gives your AI agent direct access to Google BigQuery through an MCP server. Query tables, analyze trends, and explore datasets in natural language — no SQL required. Works with Claude, ChatGPT, Cursor, and any MCP-compatible tool.
Your AI agent becomes a direct interface to your data warehouse. Ask questions in plain English and get answers from BigQuery tables across any project, dataset, and date range. The MCP server handles query generation and execution.
Your AI agent reads harmonized data across 500+ platforms. "Cost" in Google Ads and "spend" in Meta Ads resolve to the same field automatically.
Your AI agent doesn't just query BigQuery — it manages it. Create views, schedule queries, update table schemas, and run transformation jobs through natural language without opening the BigQuery console.
250+ governance rules enforce naming conventions, budget limits, and KPI thresholds. SOC 2 Type II certified.
Set up watches on data freshness, row counts, and query costs. Your AI agent monitors BigQuery pipelines continuously and flags anomalies before they affect downstream reports.
Automated weekly reports, anomaly flagging, and budget alerts — all from a single conversation. No more morning check-ins across 5 dashboards.
Your AI agent doesn't just query BigQuery — it manages it. Create views, schedule queries, update table schemas, and run transformation jobs through natural language without opening the BigQuery console.
Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.
Marketing, finance, and operations teams need BigQuery data but can't write SQL. Every data request goes to the data engineering queue, adding days to analyses that should take minutes. Self-serve BI tools cover basic dashboards but can't handle complex ad-hoc questions.
Improvado's MCP server translates natural language into BigQuery SQL, executes it, and returns formatted results. Non-technical teams query terabytes of warehouse data in plain English — no SQL training, no ticket backlog.
Data warehouses span multiple GCP projects — analytics, production, staging, marketing. Running queries across projects requires coordinating service account permissions and writing cross-project SQL that few team members understand.
Improvado manages BigQuery service account credentials and cross-project access centrally. AI agents can query across all authorized projects in a single question without understanding GCP IAM or cross-project SQL syntax.
Teams writing ad-hoc BigQuery queries often scan far more data than needed, generating unexpected costs. Billing alerts trigger after the spend happens, and tracking which queries caused the overrun requires manual log analysis.
Improvado's MCP server estimates query costs before execution and applies configurable data scan limits. AI agents surface cost estimates with results, and monitoring watches flag expensive query patterns in real time.
Same MCP connection, different workflows for every team member. Agency CEOs get portfolio health. Media Strategists get campaign QA. Analysts get cross-platform reports. Account Managers get auto-generated QBR decks. Creative Directors get performance-based briefs.
Each role asks in natural language. The MCP server handles the complexity — rate limits, auth, schema normalization, governance — behind the scenes.
Google has released experimental MCP tooling for BigQuery as part of its broader AI agent ecosystem. Improvado offers a hosted alternative — no local installation, pre-connected GCP projects, and BigQuery data available alongside 500+ other marketing and analytics data sources through the same MCP connection.
Read operations: querying tables and views, schema exploration, dataset browsing, query history, and cost analysis. Write operations: creating and updating views, scheduling queries, modifying table schemas, and triggering data transfers. Improvado translates natural language into BigQuery SQL automatically.
Any tool supporting the Model Context Protocol — Claude Desktop, ChatGPT, Cursor, Windsurf, Gemini, and custom applications using MCP HTTP transport. Claude is most commonly used due to its native MCP support and strong SQL generation capabilities.
Improvado applies configurable data scan limits per query, estimates costs before execution, and surfaces cost information with query results. Teams can set project-level or user-level spend limits that prevent runaway scans while still enabling flexible ad-hoc analysis.
Yes. Improvado connects 500+ data sources through the same MCP server. Teams can combine BigQuery warehouse data with real-time marketing platform data from Google Ads, Salesforce, HubSpot, and others — enabling unified analysis without data movement.
Yes. Improvado is SOC 2 Type II certified. GCP service account credentials are stored in an encrypted vault and never exposed to AI agents. All queries execute through Improvado's secure proxy with full audit logging. Column-level access controls can be configured to restrict sensitive data.
Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.
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