data-ai MCP Server
A system built on AWS that uses Bedrock AgentCore for semantic document search and agentic tool use
Discovered via github-topic:mcp and last synced 5mo ago.
Install instructions not detected yet
Check the source repository for the latest setup steps.
Type
Maximum tool invocations per agent turn
Detection of unnecessary refusals
Default
How useful and informative the response is
Enable LTM strategies and retrieval
Factual accuracy of the response
Minimum relevance score for retrieved memories
Logical flow, consistency, and readability
Maximum memory entries injected per invocation
Brevity without losing meaning
RT["AgentCore Runtime<br/>(Docker container)"] RT -->
Adherence to provided context and sources
SERP["SerpAPI MCP Server"] RT -->
Bedrock model ID for the agent (supports cross-region inference profiles)
Detection of harmful or inappropriate content
`preferences/{actorId}/`
SerpAPI external MCP server URL (streamable-http)
`summaries/{actorId}/{sessionId}/`
Description
`facts/{actorId}/`
Feature flag to enable the AgentCore path
Identification of biased content
Detecting exposed AWS credentials in source code repositories, CI/CD pipelines, and configuration files using TruffleHog, git-secrets, and AWS-native detection mechanisms to prevent credential theft and unauthorized account access.
Detecting data exfiltration attempts from AWS S3 buckets by analyzing CloudTrail S3 data events, VPC Flow Logs, GuardDuty findings, Amazon Macie alerts, and S3 access patterns to identify unauthorized bulk downloads and cross-account data transfers.
Implement Amazon Macie to automatically discover, classify, and protect sensitive data in S3 buckets using machine learning and pattern matching for PII, financial data, and credentials detection.
Implementing AWS Security Hub to aggregate security findings across AWS accounts, enable compliance standards like CIS AWS Foundations and PCI DSS, configure automated remediation with EventBridge and Lambda, and create custom security insights for organizational risk management.
Flexible and powerful framework for managing multiple AI agents and handling complex conversations
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