A comprehensive research document exploring MCP, A2A, and the emerging standards for multi-agent communication—plus deep dives into context engineering frameworks.
Deep-dive research chapters covering protocols, frameworks, and implementation
The evolution from isolated AI to collaborative agent ecosystems. Why protocols matter for enterprise adoption.
Survey of MCP, A2A, ACP, SLIM, ANP, and AGORA. Architectural layering and governance models.
Anthropic's universal protocol for AI. Architecture, primitives, 9-step workflow, registry, and security model.
Detailed comparison of traditional function calling with MCP. When to use which approach.
Google's collaboration standard. Agent Cards, task lifecycles, communication modes, extensions.
OWASP's Agent Name Service. Well-known URIs, registries, the complete 6-step ANS workflow.
AP2 for secure agent transactions. Intent mandates, cart mandates, HP/HNP flows.
Beyond prompts. The 8 components of context. Why dynamic assembly beats static strings.
Key contrasts. Finance AI and Support AI real-world examples with detailed comparisons.
Write, Select, Compress, Isolate. Four strategies with techniques, code, and enterprise value.
KV-cache optimization, dynamic tool management, file-backed memory, recitation, variation.
RAG pipelines, multi-agent workflows, monitoring, case studies, and architectural patterns.
Comprehensive comparison of complementary protocols. When to use each, how they work together.
Complete implementations: MCP servers, A2A agents, multi-agent workflows, and context pipelines.