list_schemas

// WHEN AI AGENTS USE THIS TOOL

AI agents call list_schemas to retrieve information from Amazon Redshift MCP Server without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

// WHY ENFORCE A POLICY ON LIST_SCHEMAS

Even though list_schemas only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

// RECOMMENDED POLICY

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

amazon-redshift-mcp-server.yaml

tools:
  list_schemas:
    rules:
      - action: allow

See the full Amazon Redshift MCP Server policy for all 6 tools.

// DETAILS

Tool Name list_schemas

Category Read

MCP Server Amazon Redshift MCP Server MCP Server

Risk Level Low

// MORE AMAZON REDSHIFT MCP SERVER TOOLS

Execute execute_query Read list_clusters Read list_columns Read list_databases Read list_tables

// WHAT CAN GO WRONG

Agents calling read-class tools like list_schemas have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

// OTHER READ TOOLS ACROSS MCP SERVERS

Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.

Firecrawl Web Scraping Server firecrawl_check_crawl_status Firecrawl Web Scraping Server firecrawl_crawl Firecrawl Web Scraping Server firecrawl_deep_research Firecrawl Web Scraping Server firecrawl_extract Firecrawl Web Scraping Server firecrawl_map Firecrawl Web Scraping Server firecrawl_scrape

// RELATED READING

// FAQ

What does the list_schemas tool do? +

List all schemas in a specified database within a Redshift cluster. This tool queries the SVV_ALL_SCHEMAS system view to discover all schemas that the user has access to in the specified database, including local schemas, external schemas, and shared schemas from datashares. ## Usage Requirements - Ensure your AWS credentials are properly configured (via AWS_PROFILE or default credentials). - The cluster must be available and accessible. - Required IAM permissions: redshift-data:ExecuteStatement, redshift-data:DescribeStatement, redshift-data:GetStatementResult. - The user must have access to the database to query system views. ## Parameters - cluster_identifier: The unique identifier of the Redshift cluster to query. IMPORTANT: Use a valid cluster identifier from the list_clusters tool. - schema_database_name: The database name to list schemas for. Also used to connect to. IMPORTANT: Use a valid database name from the list_databases tool. ## Response Structure Returns a list of RedshiftSchema objects with the following structure: - database_name: The name of the database where the schema exists. - schema_name: The name of the schema. - schema_owner: The user ID of the schema owner. - schema_type: The type of the schema (external, local, or shared). - schema_acl: The permissions for the specified user or user group for the schema. - source_database: The name of the source database for external schema. - schema_option: The options of the schema (external schema attribute). ## Usage Tips 1. First use list_clusters to get valid cluster identifiers. 2. Then use list_databases to get valid database names for the cluster. 3. Ensure the cluster status is 'available' before querying schemas. 4. Note schema types to understand if they are local, external, or shared. 5. External schemas connect to external data sources like S3 or other databases. ## Interpretation Best Practices 1. Focus on 'local' schema types for cluster-native schemas. 2. 'external' schema types indicate connections to external data sources. 3. 'shared' schema types indicate schemas from datashares. 4. Use schema names for subsequent table and column discovery. 5. Consider schema permissions (schema_acl) for access planning.. It is categorised as a Read tool in the Amazon Redshift MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on list_schemas? +

Add a rule in your Intercept YAML policy under the tools section for list_schemas. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Amazon Redshift MCP Server MCP server.

What risk level is list_schemas? +

list_schemas is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit list_schemas? +

Yes. Add a rate_limit block to the list_schemas rule in your Intercept policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block list_schemas completely? +

Set action: deny in the Intercept policy for list_schemas. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides list_schemas? +

list_schemas is provided by the Amazon Redshift MCP Server MCP server (awslabs.redshift-mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Let agents act without letting them run wild.