温馨提示：本站仅提供公开网络链接索引服务，不存储、不篡改任何第三方内容，所有内容版权归原作者所有
AI智能索引来源：http://www.ibm.com/think/topics/model-context-protocol
点击访问原文链接

What is Model Context Protocol (MCP)? | IBM

进入原网站 导航首页
WelcomeOverviewAI agents versus AI assistantsWhat is agentic AI?Why is agentic AI important?Agentic AI versus generative AIOverviewAgentic engineeringAgentOpsTutorial: AgentOps with IBM Telemetry using watsonx OrchestrateBuilding AI agentsEvolution of AI agentsOverviewGoal-based agentModel-based reflex agentSimple reflex agentUtility-based agentOverviewWhat are agentic workflows?Tutorial: Agentic workflowsCommunicationLearningMemoryPerceptionPlanningReasoningWhat is tool calling?Tutorial: Ollama tool callingTutorial: LM Studio tool callingOverviewWhat is agent orchestration?Tutorial: Agent orchestrationHierarchical AI agentsWhat are multi-agent systems?Tutorial: crewAI multi-agent call analysisMulti-agent collaborationWhat is ReAct?Tutorial: LangGraph ReAct agentWhat is ReWOO?Tutorial: ReWOO reasoning agentOverviewWhat is ACP?Tutorial: ACP agent interoperabilityWhat is A2A protocol?Tutorial: A2A chat systemWhat is MCP?Tutorial: MCP integration with IBM BobTutorial: MCP serverOverviewWhat is agentic orchestration?Tutorial: Agent orchestrationMulti-agent collaborationTutorial: crewAI multi-agent call analysisOverviewAgentGPTWhat is AutoGen?Tutorial: AutoGen multi-agent RAGAutoGPTBabyAGIWhat is BeeAI?Tutorial: BeeAI agentic contract managementWhat is ChatDev?Tutorial: ChatDev ChatChainWhat is crewAI?Tutorial: crewAI retail shelf optimizationIBM watsonx agentsWhat is LangChain?Tutorial: LangChain agentWhat is LangGraph?Tutorial: LangGraph SQL agentTutorial: LangGraph ReAct agentWhat is Langflow?Tutorial: Custom Langflow agent with watsonx OrchestrateWhat is MetaGPT?Tutorial: Multi-agent PRD automationOverviewAI agent ethicsWhat is AI agent evaluation?Tutorial: AI agent evaluationTutorial: AI agent observabilityAI agent securityTutorial: Human-in-the-loopOverviewTutorial: LangChain agentic RAGWhat is agentic chunking?Tutorial: Agentic chunking for RAGTutorial: Corrective RAGOverviewAutomationCustomer serviceFinanceHealthcareHuman resourcesMarketingProcurementRevOpsSalesSupply chainAnna GutowskaAItoolsdatabasesmultiagent systemAI agentAI agentMultiagent systemsAI modelsLarge language models (LLMs)GranitechatbotSentiment analysisAPIsIBM Privacy Statementopen sourceREST APIsLangChainLangGraphBeeAIcrewAILLM inferencingdebugmultiagent orchestrationretrieval augmented generation (RAG)vector databasetool-callingagentic workflowsAnna GutowskaGuide Start realizing ROI: A practical guide to agentic AI Learn how to scale agentic AI for measurable ROI across your enterprise. This playbook outlines the top barriers that limit impact, how to effectively measure ROI and a practical framework to drive successful, enterprise-wide adoption. Get the guideBuild, run and manage AI agents with watsonx OrchestrateIBV Report The enterprise in 2030: Engineered for perpetual innovation Discover our five predictions about what will define the most successful enterprises in 2030, and the steps leaders can take to gain an AI-first advantage. Read the reportReport AI governance imperative: evolving regulations and emergence of agentic AI Learn how evolving regulations and the emergence of AI agents are reshaping the need for robust AI governance frameworks. Read the reportTechsplainers podcast Agentic AI explained Techsplainers by IBM breaks down the essentials of agentic AI, from key concepts to real‑world use cases. Clear, quick episodes help you learn the fundamentals fast. Listen nowGuidebook Unlock AI ROI: A tactical guide to enterprise productivity Learn proven strategies to boost productivity and power enterprise transformation with AI and innovation at the core. Read the guidebookBuyer guide How AI agents and assistants can benefit your organization Dive into this comprehensive guide that breaks down key use cases and core capabilities, providing step-by-step recommendations to help you choose the right solutions for your business. Read the guideVideo Reimagine business productivity with AI agents and assistants Learn how AI agents and AI assistants can work together to achieve new levels of productivity. Watch nowDemo Try watsonx Orchestrate® Explore how generative AI assistants can lighten your workload and improve productivity. Start the demoReport From AI projects to profits: How agentic AI can sustain financial returns Learn how organizations are shifting from launching AI in disparate pilots to using it to drive transformation at the core. Read the reportReport Omdia Report on empowered intelligence: The impact of AI agents Discover how you can unlock the full potential of gen AI with AI agents. Read the reportPodcast How AI agents will reinvent productivity Learn ways to use AI to be more creative, efficient and start adapting to a future that involves working closely with AI agents. Listen nowNews Ushering in the agentic enterprise: Putting AI to work across your entire technology estate Stay updated about the new emerging AI agents, a fundamental breaking point in the AI revolution. Read the newsPodcast The future of agents, AI energy consumption, Anthropic computer use and Google watermarking AI-generated text Stay ahead of the curve with our AI experts on this episode of Mixture of Experts as they dive deep into the future of AI agents and more. Listen nowCase study How Comparus is using a "banking assistant" Comparus used solutions from watsonx.ai® and impressively demonstrated the potential of conversational banking as a new interaction model. Read the case studyExplore watsonx OrchestrateExplore AI agent solutionsExplore artificial intelligence servicesExplore watsonx OrchestrateExplore watsonx.aihttps://modelcontextprotocol.io/introductionHuggingface.cohttps://huggingface.co/blog/Kseniase/mcphttps://modelcontextprotocol.io/docs/concepts/resourceshttps://modelcontextprotocol.io/docs/concepts/toolshttps://modelcontextprotocol.io/docs/concepts/promptsJsonrpc.orghttps://www.jsonrpc.org/specificationhttps://modelcontextprotocol.io/docs/concepts/transportshttps://doi.org/10.20944/preprints202504.0245.v1

智能索引记录