5 MCPs Every Claude Code User Should Install

Brock Mesarich | AI for Non Techies · Intermediate ·🧠 Large Language Models ·2mo ago

Skills: LLM Engineering80%Tool Use & Function Calling60%

Key Takeaways

Installs 5 essential MCPs for Claude Code, including GitHub, Gmail, Notion, Slack, and Linear, to enhance its functionality

Original Description

Most Claude Code users never connect it to anything. Which is wild because there are MCP servers that completely change what Claude can do. The five I use every day are GitHub, Gmail, Notion, Slack, and Linear. Once they're connected, Claude can manage repos, draft emails, search your Notion workspace, summarize Slack threads, and update your sprint board, all from one conversation. Each one takes about a minute to install.

Watch on YouTube ↗ (saves to browser)

Sign in to unlock AI tutor explanation · ⚡30

More on: LLM Engineering

View skill →

Build an LLM and RAG-based Chat Application using AlloyDB and LangChain

FULLY LOCAL Mistral AI PDF Processing [Hands-on Tutorial]

FULLY LOCAL Mistral AI PDF Processing [Hands-on Tutorial]

Coding a Multimodal (Vision) Language Model from scratch in PyTorch with full explanation

Coding a Multimodal (Vision) Language Model from scratch in PyTorch with full explanation

Ultimate Guide: Deploy Google ADK Agents to Vertex AI & Cloud Run (Step-by-Step Tutorial)

Ultimate Guide: Deploy Google ADK Agents to Vertex AI & Cloud Run (Step-by-Step Tutorial)

Shane | LLM Implementation

How to Make an Asteroids Game Bot (LIVE)

How to Make an Asteroids Game Bot (LIVE)

Using Claude Code + Nano Banana Pro To Create a Dataset of Engineering Drawings

Using Claude Code + Nano Banana Pro To Create a Dataset of Engineering Drawings

Automata Learning Lab

Related Reads

Open-Weight LLM API Integration: A Developer's Guide to Building with Accessible AI

Learn to integrate Open-Weight LLM APIs for accessible AI development, enabling developers to build innovative applications with ease

Dev.to · NovaStack

Nobody is home inside the machine.

Distinguish between intelligence and consciousness to better understand AI's capabilities and limitations

Stop Judging Every Run: Eval Sampling Is a Budget Decision, Not a Coverage One

Learn to optimize LLM evaluation by treating sampling as a budget decision, not a coverage requirement, to reduce costs without compromising model performance

Unlocking Open-Weight LLMs: Seamless API Integration with NovaPointAI

Integrate open-weight LLMs into Dart applications using NovaPointAI's API, eliminating the need for GPU infrastructure management

5 Levels of AI Agents - From Simple LLM Calls to Multi-Agent Systems

Dave Ebbelaar (LLM Eng)