Security is built into the protocol – servers control their own resources, there's no need to share API keys with LLM providers, and there are clear system boundaries.
CODE
-
MCP Servers: Beyond Data Sharing Tools and Prompts
By
–
An MCP server shares more than just data as well. In addition to resources (files, docs, data), they can expose:
– Tools (API integrations, actions)
– Prompts (templated interactions) -
MCP Protocol Unifies Local and Remote Resource Access
By
–
Part of what makes MCP powerful is that it handles both local resources (your databases, files, services) and remote ones (APIs like Slack or GitHub's) through the same protocol
-
MCP Architecture: Client-Server Model for Service Integration
By
–
At its core, MCP follows a client-server architecture where multiple services can connect to any compatible client. Clients are applications like Claude Desktop, IDEs, or AI tools. Servers are light adapters that expose data sources.
-
MCP: Standard Protocol for LLM External System Integration
By
–
Getting LLMs to interact with external systems isn't usually that easy. Today, every developer needs to write custom code to connect their LLM apps with data sources. It's messy, repetitive work. MCP fixes this with a standard protocol for sharing resources, tools, and prompts.
-
Claude Desktop MCP Integration Demo: GitHub Repository and Pull Request Creation
By
–
Here's a quick demo using the Claude desktop app, where we've configured MCP:
— Alex Albert (@alexalbert__) 25 novembre 2024
Watch Claude connect directly to GitHub, create a new repo, and make a PR through a simple MCP integration.
Once MCP was set up in Claude desktop, building this integration took less than an hour. pic.twitter.com/xseX89Z2PDHere's a quick demo using the Claude desktop app, where we've configured MCP: Watch Claude connect directly to GitHub, create a new repo, and make a PR through a simple MCP integration. Once MCP was set up in Claude desktop, building this integration took less than an hour.
-
Anthropic Introduces Model Context Protocol for LLM Data Integration
By
–
Introducing the Model Context Protocol (MCP) An open standard we've been working on at Anthropic that solves a core challenge with LLM apps – connecting them to your data. No more building custom integrations for every data source. MCP provides one protocol to connect them all:
-
SambaNova Cloud Empowers Developers at Every AI Journey Stage
By
–
We wanted you to hear from the team that made SambaNova Cloud possible 📣
— SambaNova (@SambaNovaAI) 25 novembre 2024
Our Director of Solutions Engineering, @ro_mattern, shares why she's excited about being able to reach #Devs at every stage of their #AI journey. 🎥
Start developing today ⤵️We wanted you to hear from the team that made SambaNova Cloud possible Our Director of Solutions Engineering, @ro_mattern
, shares why she's excited about being able to reach #Devs at every stage of their #AI journey. Start developing today -
Qwen 2 VL + FLUX: Advanced Open Source Image Generation
By
–
Qwen 2 VL + FLUX > supports variation, img2img, inpainting, and controlnet-guided generation
> depth estimation and line detection for precise structural guidance
> aspect ratios up to 1536×1024 MIT licensed! -
SmolLM: Open Source Language Model Training and Deployment
By
–
SmolLM – run, pre-train, fine-tune, evaluate SoTA fully open source LM Run with Transformers, MLX, Transformers.js, MLC Web-LLM, Ollama, Candle and more! Apache 2.0 licensed codebase – go explore now!