OGGlossary OSVocabulário de Solana reconstruído para builders.
ENPT-BRES
IA / ML

Model Context Protocol (MCP)

An open standard introduced by Anthropic in November 2024 for connecting AI applications to external data sources, tools, and workflows via a unified protocol. Often described as 'USB-C for AI,' MCP eliminates the need for custom integrations per data source. Adopted by OpenAI in March 2025 and donated to the Linux Foundation's Agentic AI Foundation. MCP handles standardized tool/data connections while agent frameworks handle orchestration.

IDmcpAliasMCP
Leitura rápida

Leitura rápida

Comece pela explicação mais curta e útil antes de aprofundar.

An open standard introduced by Anthropic in November 2024 for connecting AI applications to external data sources, tools, and workflows via a unified protocol. Often described as 'USB-C for AI,' MCP eliminates the need for custom integrations per data source. Adopted by OpenAI in March 2025 and donated to the Linux Foundation's Agentic AI Foundation. MCP handles standardized tool/data connections while agent frameworks handle orchestration.

Modelo mental

Modelo mental

Use primeiro a analogia curta para raciocinar melhor sobre o termo quando ele aparecer em código, docs ou prompts.

Pense nisso como uma peça da pilha de contexto ou inferência usada em produtos com agentes ou LLMs.

Contexto técnico

Contexto técnico

Coloque o termo dentro da camada de Solana em que ele vive para raciocinar melhor sobre ele.

LLMs, RAG, embeddings, inferência e primitivas voltadas a agentes.

Por que builders ligam para isso

Por que builders ligam para isso

Transforme o termo de vocabulário em algo operacional para produto e engenharia.

Este termo destrava conceitos adjacentes rapidamente, então funciona melhor quando você o trata como um ponto de conexão, não como definição isolada.

Handoff para IA

Handoff para IA

Use este bloco compacto quando quiser dar contexto aterrado para um agente ou assistente sem despejar a página inteira.

Model Context Protocol (MCP) (mcp)
Categoria: IA / ML
Definição: An open standard introduced by Anthropic in November 2024 for connecting AI applications to external data sources, tools, and workflows via a unified protocol. Often described as 'USB-C for AI,' MCP eliminates the need for custom integrations per data source. Adopted by OpenAI in March 2025 and donated to the Linux Foundation's Agentic AI Foundation. MCP handles standardized tool/data connections while agent frameworks handle orchestration.
Aliases: MCP
Relacionados: Agente de IA, Tool Use (Function Calling), LangChain / LangGraph
Glossary Copilot

Faça perguntas de Solana com contexto aterrado sem sair do glossário.

Use contexto do glossário, relações entre termos, modelos mentais e builder paths para receber respostas estruturadas em vez de output genérico.

Abrir workspace completa do Copilot
Explicar este código

Opcional: cole código Anchor, Solana ou Rust para o Copilot mapear primitivas de volta para termos do glossário.

Faça uma pergunta aterrada no glossário

Faça uma pergunta aterrada no glossário

O Copilot vai responder usando o termo atual, conceitos relacionados, modelos mentais e o grafo ao redor do glossário.

Grafo conceitual

Veja o termo como parte de uma rede, não como uma definição sem saída.

Esses ramos mostram quais conceitos esse termo toca diretamente e o que existe uma camada além deles.

Ramo

Agente de IA

An autonomous AI system that can plan, use tools, and take actions to accomplish goals. Agents use LLMs as the reasoning core and have access to tools (APIs, code execution, web browsing, database queries). In blockchain: agents can analyze smart contracts, execute transactions, monitor DeFi positions, and automate trading strategies. Frameworks: LangChain, CrewAI, Claude Agent SDK.

LLM (Modelo de Linguagem Grande)
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Ramo

Tool Use (Function Calling)

An LLM capability where the model generates structured calls to external tools/functions rather than just text. The model decides which tool to invoke and with what parameters. Examples: calling an API, executing code, querying a database, or reading a file. Tool use enables agents to interact with the real world. Claude, GPT-4, and Gemini support native tool use.

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Ramo

LangChain / LangGraph

LangChain is a popular open-source framework for building LLM-powered applications, providing abstractions for chains, tools, memory, and retrieval. LangGraph extends it with a graph-based runtime for building stateful, multi-step agent workflows with precise control over execution flow, state persistence, and error recovery. LangGraph is the production-grade choice for complex agentic applications requiring fine-grained state management.

CrewAI
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Próximos conceitos para explorar

Continue a cadeia de aprendizado em vez de parar em uma única definição.

Estes são os próximos conceitos que valem abrir se você quiser que este termo faça mais sentido dentro de um workflow real de Solana.

IA / ML

Agente de IA

An autonomous AI system that can plan, use tools, and take actions to accomplish goals. Agents use LLMs as the reasoning core and have access to tools (APIs, code execution, web browsing, database queries). In blockchain: agents can analyze smart contracts, execute transactions, monitor DeFi positions, and automate trading strategies. Frameworks: LangChain, CrewAI, Claude Agent SDK.

Abrir termo
IA / ML

Tool Use (Function Calling)

An LLM capability where the model generates structured calls to external tools/functions rather than just text. The model decides which tool to invoke and with what parameters. Examples: calling an API, executing code, querying a database, or reading a file. Tool use enables agents to interact with the real world. Claude, GPT-4, and Gemini support native tool use.

Abrir termo
IA / ML

LangChain / LangGraph

LangChain is a popular open-source framework for building LLM-powered applications, providing abstractions for chains, tools, memory, and retrieval. LangGraph extends it with a graph-based runtime for building stateful, multi-step agent workflows with precise control over execution flow, state persistence, and error recovery. LangGraph is the production-grade choice for complex agentic applications requiring fine-grained state management.

Abrir termo
IA / ML

Multimodal AI

AI models that can process and generate multiple data types: text, images, audio, video, and code. Modern multimodal models (GPT-4V, Claude, Gemini) can analyze screenshots of dApp UIs, read code from images, generate diagrams, and understand charts. In blockchain development, multimodal capabilities help analyze transaction visualizations, audit UI screenshots, and process documentation with images.

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Comumente confundido com

Termos próximos em vocabulário, sigla ou vizinhança conceitual.

Essas entradas são fáceis de misturar quando você lê rápido, faz prompting em um LLM ou está entrando em uma nova camada de Solana.

IA / MLreasoning-model

Reasoning Model

A class of LLMs trained with reinforcement learning to generate step-by-step internal chain-of-thought before producing a final answer, enabling stronger performance on complex math, coding, and logic tasks. Pioneered by OpenAI's o1 (September 2024) and followed by o3, DeepSeek-R1, and Claude's extended thinking mode. Unlike standard LLMs that answer directly, reasoning models produce a variable-length internal CoT, allowing controllable compute at inference time.

AliasThinking ModelAliaso1
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IA / MLcontext-window

Context Window

The maximum amount of text (measured in tokens) an LLM can process in a single interaction. Larger windows enable processing more code/documentation at once. Sizes vary: GPT-4 (128K tokens), Claude (200K tokens), Gemini (1M+ tokens). One token ≈ 4 characters in English. Context window limits affect how much codebase an AI can analyze in a single request.

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IA / MLdiffusion-model

Diffusion Model

A generative AI architecture that creates images, video, or audio by learning to reverse a noise-adding process—starting from pure noise and iteratively denoising to produce coherent output. Diffusion models power leading image generators (Stable Diffusion, DALL-E 3, Midjourney) and video generators (Sora). Key variants include latent diffusion (operating in compressed space) and diffusion transformers (DiT).

AliasLatent DiffusionAliasDiT
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Termos relacionados

Siga os conceitos que realmente dão contexto a este termo.

Entradas de glossário só ficam úteis quando estão conectadas. Esses links são o caminho mais curto para ideias adjacentes.

IA / MLagent-ai

Agente de IA

An autonomous AI system that can plan, use tools, and take actions to accomplish goals. Agents use LLMs as the reasoning core and have access to tools (APIs, code execution, web browsing, database queries). In blockchain: agents can analyze smart contracts, execute transactions, monitor DeFi positions, and automate trading strategies. Frameworks: LangChain, CrewAI, Claude Agent SDK.

Abrir termo
IA / MLtool-use

Tool Use (Function Calling)

An LLM capability where the model generates structured calls to external tools/functions rather than just text. The model decides which tool to invoke and with what parameters. Examples: calling an API, executing code, querying a database, or reading a file. Tool use enables agents to interact with the real world. Claude, GPT-4, and Gemini support native tool use.

Abrir termo
IA / MLlangchain

LangChain / LangGraph

LangChain is a popular open-source framework for building LLM-powered applications, providing abstractions for chains, tools, memory, and retrieval. LangGraph extends it with a graph-based runtime for building stateful, multi-step agent workflows with precise control over execution flow, state persistence, and error recovery. LangGraph is the production-grade choice for complex agentic applications requiring fine-grained state management.

Abrir termo
Mais na categoria

Permaneça na mesma camada e continue construindo contexto.

Essas entradas vivem ao lado do termo atual e ajudam a página a parecer parte de um grafo maior, não um beco sem saída.

IA / ML

LLM (Modelo de Linguagem Grande)

A neural network trained on vast text corpora to understand and generate human language. LLMs (GPT-4, Claude, Llama, Gemini) use transformer architectures with billions of parameters. They power chatbots, code generation, summarization, and reasoning tasks. In blockchain development, LLMs assist with smart contract writing, audit review, documentation, and code explanation.

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IA / ML

Transformer

The neural network architecture underlying modern LLMs, introduced in 'Attention Is All You Need' (2017). Transformers use self-attention mechanisms to process input sequences in parallel (unlike recurrent networks). Key components: multi-head attention, positional encoding, feedforward layers, and layer normalization. Variants include encoder-only (BERT), decoder-only (GPT), and encoder-decoder (T5).

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IA / ML

Attention Mechanism

A neural network component that allows models to weigh the relevance of different parts of the input when producing output. Self-attention computes query-key-value dot products across all positions, enabling each token to 'attend' to every other token. Multi-head attention runs multiple attention functions in parallel. Attention is O(n²) in sequence length, driving context window research.

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IA / ML

Foundation Model

A large AI model trained on broad data that can be adapted for many downstream tasks. Foundation models (GPT-4, Claude, Llama 3, Gemini) are pre-trained on internet-scale text/code and can be fine-tuned, prompted, or used via APIs for specific applications. The term emphasizes that one base model serves as the foundation for diverse use cases rather than training task-specific models.

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