AWS Redshift

Live

TRUSTED IDP

ANALYTICS

Analytics

Amazon Redshift is a fully managed cloud data warehouse that enables fast, cost-effective analysis of structured and semi-structured data at scale.

  • Acts as the user: Every tool call runs as the authorizing user. Access and audit trail stay intact.
  • Credentials stay vaulted: AES-256 encrypted, resolved at request time, never stored in LLM context.
  • Scoped before every call: Per-user permissions enforced automatically. 90-day audit trail included.
AWS Redshift
agent · Acme Q3
Run
Cancel Query in AWS Redshift
S
redshift_cancel_query
85ms
AWS Redshift agent
Cancel a running amazon redshift sql statement using its statement id..
Sources: AWS Redshift
redshiftmcp
1 tool call
18:29
Message Claude...

AWS Redshift tools for AI agents

CALL ANY TOOL
7 tools covering describe, execute, cancel.
redshift_list_tables
List tables
List tables in an Amazon Redshift database using the Redshift Data API. Supports filtering by schema and table name patterns with pagination.
Parameters
Name
Type
Required
Description
connected_database
string
Optional
Override the connected account's default database for this request.
max_results
integer
Optional
Maximum number of tables to return.
next_token
string
Optional
Pagination cursor from a previous redshift_list_tables response.
schema_pattern
string
Optional
LIKE pattern to filter schemas (e.g., public, my_schema%).
table_pattern
string
Optional
LIKE pattern to filter tables (e.g., orders, user%).
redshift_get_query_result
Get query result
redshift_list_schemas
List schemas
redshift_execute_sql
Execute sql
redshift_list_databases
List databases
redshift_describe_table
Describe table
redshift_list_statements
List statements
redshift_describe_statement
Describe statement
redshift_batch_execute_sql
Batch execute sql
redshift_cancel_query
Cancel query
Build your Agent
Same auth pattern across every framework.
Python · LlamaIndex
from langchain_mcp_adapters.client import MultiServerMCPClient
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="redshift")

mcp = MultiServerMCPClient({
"redshift": {
"url": "https://mcp.scalekit.com/redshift",
"headers": {"Authorization": "Bearer " + token}
}
})
tools = await mcp.get_tools()
import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "redshift" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/redshift
// Pass: Authorization: Bearer + token
import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "redshift" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/redshift
// Pass: Authorization: Bearer + token
from google.adk.agents import LlmAgent
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="redshift")
# Connect to MCP at https://mcp.scalekit.com/redshift
# Pass: Authorization: Bearer + token
Try these prompts
Paste any prompt into your agent to get started.
Get started
Copy the prompt
Copied
List tables in an Amazon Redshift database using the Redshift Data API?
Copy the prompt
Copied
Retrieve the results of a previously executed Redshift SQL statement using the statement ID returned by redshift_execute?
Advanced
Copy the prompt
Copied
Execute a SQL statement against Amazon Redshift using the Redshift Data API?
Copy the prompt
Copied
Describe the schema of a table in Amazon Redshift using the Redshift Data API, including column names, types, and metada?
SEE HOW AUTH WORKS
User authorises once. Every agent call after uses their token with scope enforcement.
1
Authorize
Your user connects
AWS Redshift
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
Limited to user
2
Store
Their
AWS Redshift
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
AWS Redshift
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
AWS Redshift
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
See the same per-user auth pattern across other connectors.
GTM and RevOps Teams
Revenue forecast commentary
Pulls open pipeline from Salesforce and HubSpot, calculates coverage against quota, flags at-risk stages, posts commentary to Slack, and logs every snapshot to Google Sheets.
GTM and RevOps Teams
Deal intelligence agent
Pulls recent Gong calls, scores deal risk with an LLM, cross-references the record in Attio, and DMs each owner their at-risk deals in Slack. Every read is scoped to that rep's own access.
Engineering Teams
Engineering standup agent
Pulls commits from GitHub and GitLab, tracks issue movement in Jira, and posts a per-engineer standup brief to Slack. Each engineer's activity is read on their own delegated OAuth.
GTM and RevOps Teams
Competitive intelligence briefing agent
Scans Gong calls for competitor mentions, matches each one to its Notion battlecard, and DMs every affected rep a single Slack digest per cycle. Every call runs as the PMM who owns the briefing, never a shared bot.
Test other agents
See the same per-user auth pattern across other connectors.
SALES
Deal intelligence agent
Score Gong call risk with an LLM, cross-reference the Attio record, and DM each owner their at-risk deals in Slack.
ENGINEERING
Engineering standup agent
Pull commits from GitHub and GitLab, track Jira issue movement, and post a per-engineer standup brief to Slack.
GTM
Revenue forecast agent
Score pipeline coverage against quota across Salesforce and HubSpot, post forecast commentary to Slack, log snapshots to Sheets.
GTM
Competitive intelligence briefing agent
Scan Gong calls for competitor mentions, match each one to its Notion battlecard, and DM every affected rep a single Slack digest.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
01.
Shared tokens break per-user analytics
A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential.
// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
One connector today. Ten tomorrow.
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
FAQs
Frequently Asked Questions

Does the agent access AWS Redshift as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the AWS Redshift token stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in AWS Redshift?
Yes. Pass a tool name filter to listScopedTools so the analytics agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches AWS Redshift.

What happens when a user revokes AWS Redshift access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Does SQL execution respect Redshift grants?
Yes. execute_sql and schema inspection run under the connected Redshift credential's grants, so schema and table permissions hold. Scalekit vaults the credential and scope-checks every statement pre-call.

Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""redshift"": {
""url"": ""https://mcp.scalekit.com/redshift"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.redshift]
url = ""https://mcp.scalekit.com/redshift""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""redshift"": {
""url"": ""https://mcp.scalekit.com/redshift"",
""type"": ""http""
}
}
}