MCP

As explained in Spring AI in Action

The Model Context Protocol is an open protocol for connecting AI applications with external tools and sources of contextual information.

Model Context Protocol (MCP) is an open specification for collecting associated tools, prompts, and resources into reusable modules that AI applications can share. It connects applications to external capabilities such as databases, filesystems, and APIs. section 7.0 section 7.6

MCP divides the integration into two cooperating components:

• An MCP Server accesses a resource and exposes it through one or more tools. section 7.1
• An MCP Client runs inside an AI application, retrieves the server’s tools, places them in prompt context, and invokes them for the LLM. section 7.1
• Servers can communicate through STDIO, HTTP with Server-Sent Events, or Streamable HTTP, although Spring AI 1.0.0 supports only STDIO and HTTP+SSE. section 7.1

Figure 7.1 Interactions between MCP Servers and MCP Clients

Use the interaction diagram to trace how an MCP Client discovers and invokes tools exposed by an MCP Server. section 7.1

How Spring AI in Action covers it

How deep it goes

Defines servers, clients, tool invocation, and transports, while deferring Streamable HTTP support in Spring AI 1.0.0.

Examples

Uses integrations such as PostgreSQL, GitHub, Google Maps, and Claude Desktop configurations.

What you can do after

Apply MCP via Spring AI to reuse external tools in AI applications and extend LLM functionality.

How it connects

Links LLMs, tools, prompts, resources, databases, filesystems, APIs, and Spring AI.

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Also explained in

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  Grokking AI ApplicationsThe Model Context Protocol is an open standard for discovering and invoking tools exposed by servers for use by AI applications and agents.
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  AI Agents in Action, Second EditionThe Model Context Protocol is an open protocol for connecting AI applications and models with external tools, data sources, and contextual resources.
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  Build AI-Enhanced Web AppsA standardized protocol for connecting AI applications and agents with externally provided tools, prompts, resources, and data sources.
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  Build an AI Agent (From Scratch)Model Context Protocol is an open protocol that standardizes how AI applications connect to tools, prompts, resources, and external services.
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  AI Agents and ApplicationsThe Model Context Protocol is a standard protocol for services to expose tools that AI applications can discover and access.
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  Architecting an Apache Iceberg LakehouseThe Model Context Protocol is a standardized protocol that lets large language models interact with external data, tools, and services through governed calls.
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  Building Reliable AI SystemsA protocol for connecting AI applications and agents to external data sources and tools.
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  Financial AI in PracticeMCP is a protocol for standardizing how AI models or agents interact with external tools and data sources.
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  Investing for ProgrammersA model context protocol is a standardized interface that lets AI agents connect to external data sources and retrieve data in a consistent format.
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  Introduction to Generative AI, Second EditionThe Model Context Protocol is an open standard for secure, two-way connections between external data sources, services, and AI-powered tools.
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  Authorization in ActionModel Context Protocol is a standard protocol for connecting AI applications to external tools and data sources.
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  Building Distributed Applications that WorkModel Context Protocol is a protocol for connecting language-model applications with external tools, data sources, and capabilities through a standardized interface.
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  Building LLM Applications with DSPyModel Context Protocol is a standard protocol for connecting language-model applications with external tools and data sources.

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Related concepts

• toolconfigures · A tool is an instrument or software capability that enables a person or system to perform a task, obtain information, or interact with resources.
• contractcontrasts with · An API contract is a specification of the operations, data, and behavioral expectations that govern interactions between software components.
• A2Acontrasts with · A2A is an interoperability protocol that enables software agents to discover, communicate, and coordinate with one another across systems.
• client-server architectureuses · A distributed computing pattern in which clients request services or resources from servers, which process the requests and provide results.
• N×M integration problemaddresses · The N×M integration problem is the growth in custom integrations that results when each of N applications must connect independently to each of M external systems or providers.
• schemauses · A data schema is a formal specification of the structure, fields, types, relationships, and constraints of data.

This explainer was generated by Manning's knowledge graph from the text of Spring AI in Action. The section links point to the parts of the book it draws on.