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Postgres MCP Tools for AI Agents

Let an agent discover schemas, find tables, inspect table structure, and run read-only queries in Postgres.

Available Tools

8 tools available in this integration

Postgres.DiscoverSchemas

Discover all the schemas in the postgres database.

Postgres.DiscoverTables

Discover all the tables in the postgres database when the list of tables is not known.

Postgres.ExecuteSelectQuery

You have a connection to a postgres database.

Postgres.GetTableSchema

Get the schema/structure of a postgres table in the postgres database

Postgres.ListColumns

Get the schema/structure of a postgres table in the postgres database

Postgres.ListSchemas

Discover all the schemas in the postgres database.

Postgres.ListTables

Discover all the tables in the postgres database when the list of tables is not known.

Postgres.QueryRows

You have a connection to a postgres database.

Why agent-optimized tools matter

Built for intent, not API schemas

Ask the agent to "find the tables behind our monthly revenue report and explain the columns that matter." Arcade picks the right Postgres tools without guessing schema, table, or column names.

Up to 100x fewer tokens

Postgres discovery and query results return only schemas, columns, and matching rows, so the agent can locate the data it needs without loading full tables or unrelated records into the model.

Complete the workflow end to end

Discover the schema, inspect the relevant tables, run a read-only query, compare the returned rows, and explain the result through one toolkit designed around the complete database investigation task.

Make actions predictable and controlled

Arcade tools return structured results and useful errors across users and runs. Teams can apply scope restrictions, redaction, and approval policies so agents follow the same controls every time.

Securing Postgres

The more capabilities agents get, the more useful they are. However, more capabilities bring more risks of undesired effects such as data loss and exfiltration.

This is why Arcade provides you with contextual rules that dictate how and when a tool is allowed to run. Arcade’s contextual access lets you govern tool visibility and behavior at every stage of execution and control who can see a tool, what inputs are allowed, and what comes back.

Learn about Contextual Access Policies

For Postgres, you can implement some of these policies:

Access when tools are listed for a user
  • Decide which tools an agent is allowed to see at all. A tool that is never listed cannot be called, whoever is asking.
Pre-execution before each tool call
  • Inspect the inputs a call is about to run with, and block it or send it for human approval when they fall outside what the agent should do unsupervised.
Post-execution after the tool returns
  • Redact Postgres.ExecuteSelectQuery results by removing values from columns containing passwords, access tokens, API keys, Social Security numbers, or payment card numbers before they reach the model.
  • Strip restricted table names from Postgres.DiscoverTables results when they match your secrets, credentials, payroll, or customer-data patterns, so an agent cannot discover those tables for later queries.
  • Redact default expressions and column comments containing credentials, connection strings, or internal hostnames from Postgres.GetTableSchema results before the model sees the schema.

How to use Postgres with your agent

Pick your MCP client below and follow the setup to connect an agent to your Postgres database. You’ll be ready to explore schemas and run read-only queries.

Your questions, answered

A Postgres MCP server exposes database discovery and read-only query capabilities as structured tools that an AI agent can call through the Model Context Protocol. An agent can inspect schemas and tables, read table definitions, and query rows from an authorized database.

Postgres does not provide a first-party MCP server in this integration. Arcade provides the MCP gateway and runtime around read-only Postgres access, including credential brokering, approval policies, redaction, and a consistent connection for supported clients.

Arcade agents can discover schemas and tables, inspect table structures and columns, run read-only SQL queries, and retrieve matching rows. They cannot insert, update, delete, alter database structures, or perform other write operations through this toolkit.

Arcade uses a shared Postgres API key or secret configured once for the connection. That credential must have permission to discover the available schemas and tables and execute the read-only queries your agent needs; grant it read-only database access where possible.

No. This toolkit uses one shared API key or secret configured once, rather than having each user connect a separate Postgres account. Arcade brokers the credential, and the model never receives it.

Yes. Contextual Access policies can require human approval before a Postgres call proceeds, redact fields from query results, or hide the database tools from an agent entirely. Since every action here is read-only, approval is mainly useful for controlling access to sensitive queries or data.

Arcade proxies Postgres API calls and does not persist your database content as part of normal tool execution. The shared credential is brokered and stored encrypted at rest, and the model never receives it.

Any framework or client that can connect to Arcade's MCP gateway or tool APIs works with Arcade Postgres, including LangChain, OpenAI Agents, CrewAI, Claude Desktop, Claude Code, Cursor, Visual Studio Code, Microsoft Copilot Studio, and GitHub Copilot.

Arcade refreshes access while the configured authorization remains valid. If the shared key or secret is revoked, rotated, expires, or can no longer be used, Postgres calls stop until the credential is reconnected or updated.

This integration does not add a separate Postgres quota described here. Your database server, connection settings, query execution limits, and any limits imposed by the credential still apply, so long-running or resource-intensive queries may be constrained by Postgres itself.

Ready to actually ship your agent?

Connect your agent to Postgres with a shared API key, agent-optimized tools and approval controls for consequential actions.

Build Your Agent Read the Postgres Quickstart