MCP Tools

MCP Tools and Servers for AI Workflows

Evaluate MCP tools by supported clients, authentication model, data access, reliability, and operational risk.

Decision Criteria

Supported clients and host applications

Authentication and secret handling

Read/write scope controls

Logging, auditability, and failure behavior

Maintenance status and community trust

Individual developer

Covers common development workflows without exposing unrelated systems.

Internal tools team

Gives agents structured access while keeping business logic in controlled services.

Enterprise team

Makes MCP adoption reviewable by security and platform owners.

Starting points from the NeuralStackly tool index.

development

Open-source super agent harness that orchestrates multi-agent workflows with sandboxes, memory, and built-in skills for research and automation.

productivity

Autonomous AI teammates that run workflows 24/7 across Notion, Slack, Mail, Calendar, and connected tools—no manual prompting needed after setup.

development

Cloud-native AI IDE with 2M token context, autonomous agents, and Gravity Mode for agentic coding workflows.

development

The first agentic IDE combining deep codebase understanding with real-time awareness to keep developers in flow state.

development

AI coding agent CLI from Moonshot AI ( makers of Kimi), with terminal-based coding, IDE integration via ACP, and VS Code extension.

development

Google's new protocol enabling websites to communicate directly with AI agents, replacing screenshot-based browsing with structured data interaction.

development

Viral open-source personal AI agent with 368K+ GitHub stars, a local-first gateway, tool calling, skills, and multi-channel messaging.

development

Self-improving open-source agent CLI from Nous Research with memory, cron scheduling, tools, skills, MCP, and multi-provider routing.