AI-ready API checklist: 23 items to make your API work with agents
A 23-item checklist covering discovery, documentation, auth, streaming, and security to make your API work with AI agents, with real scoring against CoinPaprika and DexPaprika.
AIエージェントと大規模言語モデル
暗号資産や市場、その基盤技術についてわかりやすく解説します。
AIエージェントと大規模言語モデルのガイド
新着順
Build an MCP server: wrap any API for AI agents in 100 lines
Step-by-step TypeScript tutorial to build a working MCP server with two tools, test it with MCP Inspector, and connect it to Claude Desktop using the free DexPaprika API.
AI agent security: prompt injection, data poisoning, and guardrails
Learn how prompt injection, data poisoning, and excessive agency threaten AI agents, with OWASP-aligned defense layers, real attack examples, and production guardrails that actually work.
Real-time data for AI agents: SSE, WebSocket, and streaming patterns
Compare SSE, WebSocket, and polling for AI agents with latency benchmarks, context window impact data, and real streaming examples from DexPaprika and CoinPaprika.
GEO: how to get your content cited by AI search engines
Learn Generative Engine Optimization: six techniques with measured citation lifts, platform-specific strategies for Perplexity/ChatGPT/Google AI Overviews, and what doesn't work.
Context windows: why AI agents forget and how to fix it
Learn what context windows are, why AI agents run out of memory during long tasks, the "lost in the middle" problem, and five strategies to manage token limits.
Multi-agent systems: when one AI agent isn't enough
Learn when multi-agent AI systems actually help vs add complexity, four architecture patterns, framework comparison, and a CEX+DEX crypto analysis example.
Vibe coding: build with AI agents instead of writing every line
What vibe coding is, when it works vs fails, security risks from real studies, and how MCP connects vibe-coded apps to live crypto data through DexPaprika.
AI agent skills: how agents self-configure with SKILL.md files
Learn how AI agent skills work, why they outperform raw documentation by 16.2 percentage points, and see real SKILL.md examples from DexPaprika's crypto API.
AI-readable APIs: the developer guide to agent-friendly design
Learn the six layers of AI-readable API design with a full DexPaprika case study: llms.txt, OpenAPI specs, MCP servers, skill files, platform integrations, and CLI tools.
AI agents in crypto and DeFi: what they actually do today
An honest assessment of crypto AI agents: which categories work (security auditing, yield optimization) and which don't (retail trading bots), with real data and examples.
RAG explained: when AI agents need retrieval over training data
Learn how retrieval-augmented generation works, when to use RAG vs fine-tuning vs long context, and see real crypto data examples with CoinPaprika and DexPaprika.
llms.txt: make your API documentation AI-readable
Learn what llms.txt is, how it differs from robots.txt, and see real implementations from CoinPaprika and DexPaprika with adoption stats and setup guidance.
Tool use in AI: how agents call APIs with real crypto examples
Learn how AI tool use works, why accuracy is still a challenge, and see real tool definitions from CoinPaprika's MCP server with live crypto data examples.
MCP explained: how AI agents connect to crypto APIs
Learn what MCP is, how it connects AI agents to tools, and see a working crypto data integration with CoinPaprika and DexPaprika MCP servers.
AI agents for crypto: how they work with real-time market data
Learn what AI agents are, how they differ from chatbots, and see a real crypto data example with CoinPaprika's free MCP server.
