"Testing Library" matching MCP servers:

Enables testing and validation of APIs for AI agent compatibility, providing scores, grades, and actionable recommendations.

MCP server providing virtual memory for AI context with durable SQLite storage, retrieval, and bounded prompt assembly to manage context windows.

Integrates Loopy's AI agent loop library with MCP-compatible clients like LM Studio, enabling discovery, analysis, crafting, and execution of bounded agent workflows.

A client library for connecting to and interacting with MCP servers hosted on smcphub.com, allowing users to find, publish, and call tools on MCP servers.

Facilitates browser automation with custom capabilities and agent-based interactions, integrated through the browser-use library.

An MCP server that integrates AI agents with MagicPod, enabling natural language control of MagicPod testing through tools like Cursor and Claude.

Enables access to agent instruction files and prompts for AI development workflows. Provides tools to retrieve and list development rules, security checks, and common prompts from an agents library through MCP protocol.

A production-ready Python library for building MCP servers with agent orchestration and domain-specific presets for platforms like GitHub, Slack, and Notion.

Enables AI agents to perform cryptocurrency trading operations on Binance exchange through 30 comprehensive tools supporting spot trading, futures contracts, options, account management, market data analysis, and risk control features. Provides enterprise-grade security with local encrypted API key storage and supports multiple account types with sandbox environment testing.

Self-hosted workspace MCP gateway that registers MCP servers, stores secrets encrypted, mints agent keys, and shares a unified tool library across multiple AI harnesses.

Enables intelligent Kubernetes deployments, automated documentation testing, organizational pattern management, and shared prompt libraries. Provides AI-powered recommendations based on cluster capabilities and automates DevOps workflows through conversational interfaces.

A lightweight server that enables AI agents to interact with the Windows operating system, allowing for file navigation, application control, UI interaction, and QA testing through various tools.

AI-native security testing platform with native MCP support, enabling automated penetration testing, vulnerability discovery, and attack-chain analysis through conversational commands.

A local reimplementation of the AWS Bedrock AgentCore Gateway with a pluggable Lambda backend for developing and testing agent-integrations offline.

A local MCP server that enables Codex and other MCP clients to orchestrate native external coding-agent harnesses through a normalized lifecycle, with guarded execution and deterministic testing.

Enables managing persistent AI workers through MCP tools for versioning, safe testing, deployment, approvals, and run lifecycle with tenant isolation and policy enforcement.

Enables managing a canonical library of agent skills and MCP servers, syncing them across multiple development harnesses, and adding, importing, or configuring them through MCP tools.

Enables interaction with a TrueRAG system through a GraphQL API using the Model Context Protocol (MCP), facilitating access to policies with a Python SDK and GQL library integration.

Enables interaction with Jellyseerr media request systems through natural language. Supports searching for media, creating requests, checking request status, and managing your media library workflow.

Manages skills and profiles on disk and probes companion tools (bob, cortex, mcphub, etc.) over stdio MCP, enabling library operations and stack readiness checks.