Agentsql
Overview
Natural-language data analyst that writes SQL, runs read-only queries, and returns charts, tables, and answers.
Agentsql is an AI data analyst for teams that want to ask questions of their database in plain English. It connects to supported databases with read-only credentials, generates SQL against the schema, runs the query, and returns a chart, table, and plain-language answer while showing the SQL for verification.
AI Agent Store research
What the evidence says about Agentsql
Agentsql focuses on closing the loop from plain-English question to executed read-only SQL result: the official page says it writes SQL, runs it read-only, and returns a chart, table, and clear answer while showing the query every time [official-product]. It is positioned for self-serve analytics over existing databases, with verified connector claims for Postgres, MySQL, Snowflake, and BigQuery [official-product].
Verified September 12, 2026
Verified capabilities
- Natural language to SQL
Users ask questions in plain English, and Agentsql writes SQL against the connected database schema.[1]
- Read-only query execution
The product runs generated SQL through a read-only connection and states that it can never write, update, or delete data.[1]
- Charts, tables, and clear answers
Agentsql returns a chart, result table, and one-line plain-English answer rather than only outputting a query string.[1]
- SQL visibility
Every answer shows the exact SQL Agentsql wrote so users or technical teammates can inspect and verify the number.[1]
- Supported database connections
The official page lists Postgres, MySQL, Snowflake, and BigQuery as supported database targets.[1]
- Plain-English refinement
Users can refine questions in natural language, such as narrowing by channel, quarter, or account type, and Agentsql rewrites and reruns the query.[1]
- Security-oriented connection model
The official page describes least-privilege read-only credentials, encryption in transit, user-controlled credentials, revocation, and a statement that it never trains on user data.[1]
Where it fits best
- Founders, operators, product managers, customer success teams, ecommerce teams, marketing teams, agencies, and analysts who need self-serve answers from operational or warehouse databases.[1]
- Teams that want non-SQL users to ask database questions in plain English while still exposing the generated SQL for technical review.[1]
- Organizations using Postgres, MySQL, Snowflake, or BigQuery and willing to connect a scoped read-only database account.[1]
Buying and deployment notes
Pricing details were not verified from the supplied official page context. The official page excerpt includes a Pricing navigation item, but no plan names, public prices, free plan, or trial terms were available in the supplied context.[1]
Platforms: Agentsql console[1]
Deployment: Connects to existing databases with read-only credentials, Postgres, MySQL, Snowflake, BigQuery[1]
Important considerations
- The supplied official context verifies connectors for Postgres, MySQL, Snowflake, and BigQuery only; teams using other databases should verify connector availability before adopting.[1]
- Agentsql requires connecting to a database with read-only, least-privilege credentials, so setup depends on the team being able to create and scope those credentials.[1]
- Pricing plan names, public prices, free-plan availability, and trial availability were not verified in the supplied official page context.[1]
Sources and research method (1)
We record only claims tied to public sources checked by our team or listing workflow. Counts above are derived directly from this profile, not a subjective rating.
- AI Data Analyst: Natural Language to SQL Answers | AgentsqlOfficial site · checked 2026-09-12
Autonomy level
50%
Comparisons
Custom Comparisons
Some of the use cases of Agentsql:
- Asking business questions in plain English
- Generating SQL from natural language
- Self-serve analytics for non-SQL teammates
- Exploring revenue, customer, product, and operations data
- Reviewing generated SQL before trusting an answer
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