MCP Tools
The most powerful integrations for AI agents
Model Context Protocol is an open standard for connecting AI to external tools.
Think of it as USB-C for AI: one universal connector for everything.
Universal
Works with Claude, ChatGPT, Cursor, Windsurf, and more
Open Source
Released by Anthropic in Nov 2024, now industry standard
Secure
Permission-aware connections with OAuth support
Composable
Combine multiple servers for powerful workflows
Your entire knowledge base at the AI's fingertips.
Semantic search across all your Notion pages and databases.
Capabilities
- Search docs with natural language
- Create and update pages
- Query databases
- Sync documentation automatically
35% reduction in search time for teams with large knowledge bases. One team reported turning a 5-page PRD into actionable Linear tasks in minutes instead of hours, with over $35k in annual productivity savings.
Design to code without screenshots.
AI reads the actual design structure: layers, auto-layout, variants, tokens.
Mind-blowing
- Generate entire web apps from designs
- Real component hierarchy, not pixels
- Access design tokens directly
- Sync design changes to code
75% reduction in UI development time. A developer reported generating an entire CRM dashboard clone from a Figma mockup: "From hours of tedious component building to minutes of AI-assisted generation."
Full access to your repositories, issues, and pull requests.
AI can manage your entire development workflow.
Capabilities
- Search code across repos
- Create and review PRs
- Manage issues and labels
- Trigger workflows and actions
Teams report AI reviewing PRs spanning 14 files across 11 services in seconds, providing consistent baseline reviews. "It catches things humans miss when fatigued, and maintains review quality across the entire codebase."
Project management for high-velocity teams.
AI becomes your sprint operations assistant.
Capabilities
- Create and update issues
- Manage projects and cycles
- Triage and prioritize backlog
- Generate status reports
30-minute task to 30 seconds. "Weekly sprint planning used to take 30 minutes of manual ticket creation. Now I describe what needs to happen and the AI creates all the issues with proper labels, assignments, and linked PRs."
Headless browser controlled by AI.
No vision models needed: uses accessibility tree for deterministic actions.
Game-changing
- Navigate and interact with any website
- Fill forms, click buttons, extract data
- Run automated tests
- Cross-browser: Chrome, Firefox, Safari
Released by Microsoft in March 2025. GitHub Copilot now uses it to verify fixes actually work. Uses the accessibility tree, not screenshots, giving AI deterministic control. "Self-healing tests that describe what they want to do, not brittle selectors."
PostgreSQL + Auth + Storage at your AI's command.
Natural language queries to your production database.
Capabilities
- Create tables and schemas
- Query data with natural language
- Deploy edge functions
- Manage authentication
70% reduction in query writing time. "I just describe what data I need in plain English and the AI writes the SQL. It understands my schema, handles joins correctly, and even suggests indexes for performance."
Your team communication, accessible to AI agents.
Automate notifications, search history, manage channels.
Capabilities
- Send and read messages
- Search conversation history
- Manage channels and users
- Automate status updates
Combine with Sentry + GitHub: Error detected → AI searches Slack for related discussions → finds context → opens PR with fix → notifies team. The AI becomes an always-on incident responder.
Deploy with a prompt.
AI can build, deploy, and manage production apps autonomously.
Capabilities
- Create new projects
- Deploy to production
- Manage environment variables
- Monitor deployments and logs
From code generation to deployment in the same conversation. "I asked for a landing page, the AI built it, tested it locally, and deployed it to Vercel, all in one chat session. The URL was live before I finished my coffee."
Error tracking meets AI debugging.
AI can see errors, analyze stack traces, and suggest fixes.
Capabilities
- Surface errors and exceptions
- Analyze performance metrics
- Correlate errors with deployments
- Generate fix recommendations
Alert to analysis: minutes to seconds. "Before, I'd get a Sentry alert, context-switch, dig through stack traces. Now the AI surfaces the error, correlates it with the recent commit, and has a fix suggestion ready before I even look at my phone."
The Composable AI Stack
MCP turns isolated tools into a unified, AI-native development platform.
Design in Figma → Code with GitHub → Deploy to Vercel → Monitor with Sentry
All orchestrated by a single AI agent.