Connecting AI Assistants to Tools, Data, APIs, and Workflows
MCP for Developers is a practical, technically rigorous guide to the Model Context Protocol: the emerging standard for connecting AI assistants to external systems.
Instead of treating MCP as magic tool-calling glue, this book teaches it as a boundary design discipline. You will learn how hosts, clients, and servers fit together; how tools, resources, and prompts differ; how transports and lifecycle negotiation work; how to build and test servers; and how to approach authorization, prompt injection, tool poisoning, local execution, observability, and production rollout.
The book is written for developers, platform engineers, AI product engineers, and security-minded technical leads who want to expose real capabilities to AI assistants without losing control of data, actions, and workflows.
Topics include:
- MCP architecture, JSON-RPC, capabilities, and lifecycle
- Tool design with schemas, structured output, idempotency, and approval
- Resources, URI patterns, context minimization, and subscriptions
- Prompt templates, elicitation, sampling, roots, and workflow boundaries
- stdio vs Streamable HTTP transports
- Building MCP servers and clients with SDKs and the MCP Inspector
- OAuth-shaped authorization, per-client consent, and token audience separation
- Prompt injection, tool poisoning, SSRF, session hijacking, and local server risks
- Production patterns for observability, reliability, schema evolution, registries, apps, and tasks
If you are building AI assistants that need to work with real systems, this book will help you design MCP integrations that are useful, understandable, and safer to operate.
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Paperback. Condition: new. Paperback. Connecting AI Assistants to Tools, Data, APIs, and Workflows MCP for Developers is a practical, technically rigorous guide to the Model Context Protocol: the emerging standard for connecting AI assistants to external systems. Instead of treating MCP as magic tool-calling glue, this book teaches it as a boundary design discipline. You will learn how hosts, clients, and servers fit together; how tools, resources, and prompts differ; how transports and lifecycle negotiation work; how to build and test servers; and how to approach authorization, prompt injection, tool poisoning, local execution, observability, and production rollout. The book is written for developers, platform engineers, AI product engineers, and security-minded technical leads who want to expose real capabilities to AI assistants without losing control of data, actions, and workflows. Topics include: - MCP architecture, JSON-RPC, capabilities, and lifecycle- Tool design with schemas, structured output, idempotency, and approval- Resources, URI patterns, context minimization, and subscriptions- Prompt templates, elicitation, sampling, roots, and workflow boundaries- stdio vs Streamable HTTP transports- Building MCP servers and clients with SDKs and the MCP Inspector- OAuth-shaped authorization, per-client consent, and token audience separation- Prompt injection, tool poisoning, SSRF, session hijacking, and local server risks- Production patterns for observability, reliability, schema evolution, registries, apps, and tasks If you are building AI assistants that need to work with real systems, this book will help you design MCP integrations that are useful, understandable, and safer to operate. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798198203679
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Taschenbuch. Condition: Neu. Neuware - Connecting AI Assistants to Tools, Data, APIs, and Workflows MCP for Developers is a practical, technically rigorous guide to the Model Context Protocol: the emerging standard for connecting AI assistants to external systems. Instead of treating MCP as magic tool-calling glue, this book teaches it as a boundary design discipline. You will learn how hosts, clients, and servers fit together; how tools, resources, and prompts differ; how transports and lifecycle negotiation work; how to build and test servers; and how to approach authorization, prompt injection, tool poisoning, local execution, observability, and production rollout. The book is written for developers, platform engineers, AI product engineers, and security-minded technical leads who want to expose real capabilities to AI assistants without losing control of data, actions, and workflows. Topics include: - MCP architecture, JSON-RPC, capabilities, and lifecycle- Tool design with schemas, structured output, idempotency, and approval- Resources, URI patterns, context minimization, and subscriptions- Prompt templates, elicitation, sampling, roots, and workflow boundaries- stdio vs Streamable HTTP transports- Building MCP servers and clients with SDKs and the MCP Inspector- OAuth-shaped authorization, per-client consent, and token audience separation- Prompt injection, tool poisoning, SSRF, session hijacking, and local server risks>If you are building AI assistants that need to work with real systems, this book will help you design MCP integrations that are useful, understandable, and safer to operate. Seller Inventory # 9798198203679