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BREAKING ๐จ: Claude got MCP support for desktop apps! Developers can use it to allow Claude to interact with local apps through "Model Context Protocol" ๐ https://t.co/AJWjAHvMjq pic.twitter.com/eP5JnhZYLx
— ๐จ AI News | TestingCatalog (@testingcatalog) 25 novembre 2024
BREAKING : Claude got MCP support for desktop apps! Developers can use it to allow Claude to interact with local apps through "Model Context Protocol"
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Announcing new open-source Python package: aisuite! This makes it easy for developers to use large language models from multiple providers. When building applications I found it a hassle to integrate with multiple providers. Aisuite lets you pick a "provider:model" just by
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Like LSP did for IDEs, we're building MCP as an open standard for LLM integrations. Build your own servers, contribute to the protocol, and help shape the future of AI integrations:
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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.
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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.
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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:
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sry thanks for following up! for classification: id do accuracy, that should be pretty straightforward. if that doesnt work would be curious to hear more! second is harder, but id use LLM-as-a-judge. you can define either a ground truth example to compare with, or just
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๐ฆ๐๐ฎ๐๐ฒ ๐ผ๐ณ ๐๐ป๐๐ฒ๐ฟ๐ฝ๐ฟ๐ถ๐๐ฒ ๐๐ ๐ฎ๐ฌ๐ฎ๐ฐ: ๐๐ป๐๐ต๐ฟ๐ผ๐ฝ๐ถ๐ฐ ๐ฒ๐ฎ๐๐ถ๐ป๐ด ๐๐ฝ ๐ข๐ฝ๐ฒ๐ป๐๐, ๐๐ด๐ฒ๐ป๐๐ ๐ฟ๐ฎ๐บ๐ฝ ๐๐ฝ ๐๐ผ ๐ญ๐ฎ% ๐ผ๐ณ ๐๐๐ฒ-๐ฐ๐ฎ๐๐ฒ๐, ๐ผ๐ฝ๐ฒ๐ป ๐บ๐ผ๐ฑ๐ฒ๐น๐ ๐บ๐ฎ๐ธ๐ฒ ๐ญ๐ต% ๐ผ๐ณ ๐๐๐ฎ๐ด๐ฒ @MenloVentures surveyed 600 enterprise IT decision-makers
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What are ya waiting for? https://
github.com/huggingface/sm
ollm
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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!