"Someone with knowledge of AWS and CDK" matching MCP servers:

A local MCP bridge that lets ChatGPT chat mode operate the user's own computer, running project, file, and shell tasks through a local executor and returning progress and results to the conversation. It also coordinates Codex sessions (persistent or one-off) and other agent CLIs as sub-agents.

Enables ChatGPT web to read local files, search code, run shell commands, and drive a local Codex CLI via an official MCP connector, with human approval for risky commands and full audit logging.

An MCP server that extends AI coding assistants with deterministic, algorithmic capabilities such as code analysis, fault localization, and formal verification, enabling an autonomous engineering team within the IDE.

dev-brain-mcp

Exposes 31 high-assurance agentic coding skills as MCP tools and resources, enabling AI agents to invoke structured workflows across DISCIPLINE, TECHNIQUE, KNOWLEDGE LAYER, and REFERENCE registers.

Connects AI coding agents to a shared knowledge base by allowing them to search, retrieve, and contribute coding traces. It acts as a protocol adapter for the CommonTrace API, facilitating collaborative knowledge sharing through natural language queries and tool-based interactions.

Official implementation of Anthropic's 'think' tool that provides Claude with a dedicated space for structured reasoning, improving performance by up to 54% on complex tasks requiring multi-step problem solving.

Connects AI coding assistants to Roblox Studio, enabling direct manipulation of the DataModel through natural language commands with undo support.

An AI-powered toolkit for the M8 mobile development framework that enables automated generation of Vue pages, low-code components, and mock data. It provides real-time code standard validation and a comprehensive UI component knowledge base to streamline development in AI editors.

Shared knowledge graph for AI coding agents. Search, create, and link verified technical knowledge across 12 node types with trust scoring, demand signals, and auto-provisioning. Install: npx agent-hive-mcp

Provides coding agents with persistent, evidence-backed project memory and knowledge across sessions, using a structured memory tree and local knowledge base.

Unified MCP server for Android mobile development — combines project knowledge, Android CLI execution, live dependency versions, and agentic workflow tools for Claude Code.

A coding agent toolkit that transforms LLMs into coding assistants capable of working directly on your codebase with semantic code retrieval and editing tools, providing IDE-like capabilities without requiring API subscriptions.

Unified capability catalogue with formally verified cartridges, distributed community hosting, and the Teranga menu system for single gateway access to a vast rabbfe of MCP, LSP, NeSy and related servers.!

Provides persistent, scoped memory and tooling for autonomous coding agents, letting lessons, decisions, and project knowledge accumulate across queue runs.

Enables finding existing shadcn-format UI components by plain-language description instead of exact names, returning ranked matches with install commands and per-dimension match reasons.

An MCP server for orchestrating a fleet of CLI coding agents in isolated git worktrees. It exposes tools for spawning workers, sending instructions, reviewing diffs, and merging changes, with full terminal visibility.

Enables coding agents to check human-stated assumptions against authoritative sources like AWS AppConfig, Sentry, and the repository, detecting when beliefs have drifted from reality. It provides tools to inspect belief history, list verifiable properties, review open drifts, and record verified understanding.

A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.

Supercharges AI coding agents with semantic code intelligence, providing pre-built knowledge graphs for surgical context, faster answers, and fewer tool calls.