"Understanding AWS EC2 Pricing" matching MCP servers:

🤖 Enable AI assistants (Claude, Cursor) to monitor, diagnose, and query Amazon Redshift using this MCP server and the AWS Data API.

Give your AI assistant real-time LLM/VLM knowledge. Pricing, benchmarks, and recommendations — updated every hour, not every training cycle.

Provides brain-inspired long-term memory for MCP clients, enabling persistent user understanding across sessions with Chinese-optimized hybrid retrieval and evolving user profiles.

Enables interaction with MySQL databases (including AWS RDS and cloud instances) through natural language. Supports database connections, query execution, schema inspection, and comprehensive database management operations.

Cline MCP integration that allows users to save, search, and format memories with semantic understanding, providing tools to store and retrieve information using vector embeddings for meaning-based search.

A server that enables LLMs like Claude to query AWS DynamoDB databases through natural language requests, supporting table management, data querying, and schema analysis.

MCP Compass is a discovery and recommendation service that assists AI assistants in finding and understanding Model Context Protocol servers through natural language queries.

Provides seamless access to Grok AI's capabilities (chat completion, image understanding, and function calling) directly from Cline via the Model Context Protocol.

An MCP server that enables users to retrieve information from AWS Knowledge Bases using RAG (Retrieval-Augmented Generation) via Bedrock Agent Runtime.

An AI-powered chatbot that researches and tracks LLM inference pricing across providers, stores structured pricing data locally, and answers pricing questions via natural language.

Enables AI assistants to access contextual knowledge from multiple repositories through Sequa's Contextual Knowledge Engine. Provides architecture-aware code understanding and cross-repository context for more accurate, production-ready code generation.

A Model Context Protocol server that enhances AI agents by providing deep semantic understanding of codebases, enabling more intelligent interactions through advanced code search and contextual awareness.

Connects MCP clients to databases like Snowflake, BigQuery, and Databricks through Alkemi's data platform, enabling natural language database queries with proper schema understanding and metadata management for consistent team-wide access.

An MCP server that gives AI agents structured code understanding and precise code intelligence via local indexing of AST, call graphs, and semantic search.

MCP server that provides secure access to a serverless Markdown wiki on AWS, enabling AI assistants to read, search, and edit pages with space-level permission checks and Bedrock-powered semantic search.

An intelligent codebase processing server that provides agentic RAG capabilities for code repositories, enabling semantic search and contextual understanding through self-evaluating retrieval loops.

Enables MCP-compatible clients to search a shared ChromaDB-backed PDF document store and generate grounded, citation-aware answers through AWS Bedrock, without calling the REST API.

A lightweight, zero-configuration MCP server for source code analysis with GraphRAG capabilities, enabling structural understanding and efficient code completion from MCP-compatible AI tools.

Provides hybrid (BM25 + vector) search over Terraform AWS and Google provider documentation, with tools for ranked search and full document retrieval.

Enables management and invocation of AWS Bedrock managed prompts with support for variable substitution, streaming responses, batch processing, and multiple AI models including Claude, Titan, Llama, and Mistral.