Build Your First MCP Server in Python
A step-by-step Python tutorial for building, running, testing, and hardening a small MCP server with a typed tool.
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MCP Tools Explained: How AI Agents Take Action
A practical guide to MCP tools, including schemas, discovery, execution, approvals, errors, and safe production design.
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MCP Transports: STDIO vs Streamable HTTP
Understand how MCP messages travel over STDIO and Streamable HTTP and how to choose the right transport for local and remote servers.
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MCP Resources Explained: Giving Agents the Right Context
Understand MCP resources, resource URIs, templates, discovery, reading, subscriptions, and safe context selection.
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MCP Lifecycle and Capability Negotiation
A current guide to MCP version compatibility, capability discovery, request metadata, feature use, and the transition from older handshakes.
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MCP Prompts Explained: Reusable Workflows for AI Applications
A practical guide to MCP prompts, including discovery, arguments, message content, user control, safety, and design patterns.
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Caching Strategies for AI Agent Systems
Reuse expensive results only when identity, freshness, authorization, and side-effect semantics make reuse safe.
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Model Routing for AI Agents
Choose models by task requirements, policy, quality, latency, and cost instead of sending every step to one default.
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Context and Token Cost Optimization
Build focused model context that preserves decision-relevant information while removing repeated and irrelevant tokens.
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AI Agent Cost Optimization
Control the cost of successful agent outcomes, not merely the price of one model call.
