"AWS Secrets Manager" matching MCP servers:

Provides a chat interface with natural language processing to deploy and manage AWS resources through an integrated Model Context Protocol (MCP) server.

This server implements the Multi-Agent Conversation Protocol for AWS SecurityHub, enabling interaction with AWS SecurityHub API through natural language commands.

Provides prompt injection detection, PII/secrets redaction, and an audit trail for AI agents via MCP tools.

Provides file-level exclusive locking across multiple Claude Code instances to prevent edit conflicts when multiple agents edit the same project simultaneously.

Start, observe, and interact with Claude Managed Agents from any MCP client — launch an agent, watch its events, reply, approve the tools it wants to run, and stop it. Runs over stdio, HTTP, or AWS Lambda with pluggable auth.

Provides secure OAuth2-based credential management for MCP servers, allowing agents to obtain short-lived token references without exposing raw secrets.

Controls local purplemux (tmux + LLM workspace manager) from Claude Code/Codex, enabling cross-LLM orchestration by managing workspaces, tabs, terminals, and Electron browser via 16 tools.

An MCP server for using Bitwarden Secrets Manager as durable credential storage for agent workflows, enabling secure secret storage, retrieval, and injection into trusted executables.

Tracks meeting commitments, verifies completion via Slack/email/Linear, and sends escalating nudges with manager escalation when deadlines slip.

Enables AI agents to make authenticated API calls and run commands with secrets injected, while keeping credentials completely hidden from the model, with policy enforcement, grants, and audit logging.

MCP server for AWS SSO authentication and profile management, enabling AI assistants to check identity, switch profiles, and manage EC2/EKS resources.

The industry-standard persistent memory and state manager for long-running agentic workflows.

This MCP server enables agents to manage complex tasks by providing tools for registration, complexity assessment, breakdown into subtasks, and status tracking throughout the task lifecycle.

MCP Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like developer behavior in reasoning AI systems.

Enables AI agents to deploy applications to AWS with DevOps capabilities by automatically inferring infrastructure needs from code and generating inspectable Infrastructure as Code specifications.

Enables AI agents to manage secrets and credentials from a secure vault via MCP tools over stdio.

Orchestrates multiple AI agents (Product Manager, Software Architect, Engineer, QA, Reviewer) to collaboratively plan, design, implement, review, and improve software development projects via MCP tools.

Enables management and provisioning of AWS resources like EC2, S3, and RDS using natural language prompts through the Model Context Protocol. It allows users to automate complex infrastructure tasks, such as setting up VPCs and security groups, via a chat interface.

Enables AI agents to manage tasks through a board with backlog, ready, in-progress, and done columns, plan daily work, track velocity, forecast backlog completion, and leverage rule-based or DeepSeek-powered recommendations.

A server that transforms a standard Language Model into a dynamic multi-agent system where the model simulates both a Conductor (project manager) and Experts (specialized agents) to tackle complex problems through a collaborative workflow.