Why multi-agent AI systems fail at context
Up to 86.7% of multi-agent AI runs fail. Most failures trace back to how agents share context, not the agents themselves. Here's why and how to fix it.
Definition
MCP (Model Context Protocol): An open protocol that standardizes how AI applications provide context and tools to language models.
Up to 86.7% of multi-agent AI runs fail. Most failures trace back to how agents share context, not the agents themselves. Here's why and how to fix it.
New research analyzed 3,282 MCP bug reports across GitHub. The patterns reveal a context delivery problem, not a protocol problem. Here's what it means.
88% of organizations report AI agent security incidents. The root cause is a context engineering failure: agents get all-or-nothing access, not scoped context.
94% of IT leaders fear vendor lock-in. Every AI tool traps your context in its own silo. Here's why your AI doesn't remember you, and what's changing.
From copy-paste to context platforms, five approaches to giving AI access to your data. Covers security trade-offs, cost, and practical recommendations.
Over 17,000 MCP servers exist but most are generic dev tools. Here's how to create a custom one for your own data without writing a single line of code.