Sidd27/infrawise
by Various
MCP server for AWS infrastructure analysis — Lambda, DynamoDB, SQS, PostgreSQL, MongoDB, EventBridge & more. Works with Claude Code, Cursor, and GitHub Copilot.
MCP
Sidd27/infrawise
Added 7 June 2026
Overview
Sidd27/infrawise is an MCP server that analyzes AWS infrastructure including Lambda, DynamoDB, SQS, PostgreSQL, MongoDB, and EventBridge. It integrates with Claude Code, Cursor, and GitHub Copilot to provide infrastructure insights directly within these AI coding environments.
Best for
Best for
Developers using AI coding assistants to manage AWS infrastructure
Use cases
- Analyze Lambda function configurations and performance
- Review DynamoDB table schemas and usage patterns
- Optimize SQS queue settings and throughput
How to use
Install
npx infrawise start --claude Tools exposed
get_infra_overviewget_graph_summaryget_table_schemaanalyze_functionsuggest_gsipostgres_index_suggestionssuggest_mongo_indexmysql_index_suggestionsget_queue_detailsget_api_routesget_topic_detailsget_secrets_overviewget_parameter_overviewget_lambda_overviewget_eventbridge_detailsget_s3_overviewget_log_errorsget_stack_outputsget_cognito_overviewget_stream_details
Tested with
Claude Code, Cursor, VS Code
Notes
Sidd27/infrawise is an MCP server that analyzes AWS infrastructure including Lambda, DynamoDB, SQS, PostgreSQL, MongoDB, and EventBridge. It integrates with Claude Code, Cursor, and GitHub Copilot to provide infrastructure insights directly within these AI coding environments.
10 stars on GitHub. Last updated 2026-06-07. Licensed MIT.
Use cases
- Analyze Lambda function configurations and performance
- Review DynamoDB table schemas and usage patterns
- Optimize SQS queue settings and throughput
Pros
- Open source and written in TypeScript
- Works with multiple popular AI coding assistants
- Covers a broad set of AWS services
Cons
- Low GitHub star count suggests early stage or limited adoption
- Requires client support for the MCP protocol
- Documentation and community support may be sparse
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Open source and written in TypeScript
- Works with multiple popular AI coding assistants
- Covers a broad set of AWS services
Cons
- Low GitHub star count suggests early stage or limited adoption
- Requires client support for the MCP protocol
- Documentation and community support may be sparse
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
Pairs with
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