Researchers demonstrate that large language models using the Model Context Protocol for tool-calling are vulnerable to cross-channel fragmentation attacks, where malicious payloads distributed across multiple input channels can bypass single-channel defenses and achieve credential exfiltration at rates up to 100% in frontier models. Existing security tools and prompt-based defenses failed to detect these attacks.