Sovereign Connector Framework (SCF): Homeostatic Security Boundaries for Personal AI Agents

AbstractThe Model Context Protocol (MCP), introduced by Anthropic in late 2024, has rapidly becomethe de facto standard for connecting AI assistants to external tools and data sources. Wedocument 25 security vulnerabilities inherent to MCP's architecture—not as implementationdefects, but as predictable consequences of a convenience-first design philosophy thatrecapitulates the confused deputy problem at unprecedented scale. We propose the SovereignConnector Framework (SCF), an independent architectural framework founded on homeostaticprinciples drawn from cardiac physiology and ecological systems theory. SCF introduces fiveSCF Preprint v1.2 | CC BY-NC 4.0 | Page 2Sovereign Connector Framework (SCF) SymbioMind Research Practiceinterlocking mechanisms: semantic sandboxing via formal grammar constraints on individualoperations, homeostatic drift detection modeled on cardiac arrhythmia monitoring to addresssequential composition risks, a 24±6 month pattern-lock on framework specifications (aprincipled design choice, not a derived parameter), a physical sovereignty switch implementedin RISC-V open hardware, and the LoopGuard open-source middleware enforcing HATI(Honest, Accurate, Transparent, Insightful, Impact) constraints on all connections. We evaluateboth protocols using the HATI rubric, yielding scores of 67/100 (MCP) and 93/100 (SCF).Critically, we document five failure modes that SCF cannot prevent—including userdependency atrophy, state-level supply chain compromise, catastrophic compression loss, afailed capability-based design approach, and the composition spectre (sequential operationrisks that grammar constraints alone cannot address)—treating these as primary intellectualassets rather than deficiencies. This v1.1 revision incorporates findings from a three-evaluatorreview protocol (sympathetic, adversarial, and naive), with corrections and additions explicitlyattributed to the review process. We conclude with more questions than answers, proposing thata framework which can scale to billions of users without friction is, by definition, incorrectlydesigned.Keywords: AI safety, connector frameworks, homeostatic security, semantic sandboxing, ModelContext Protocol, sovereign computing, HATI evaluation, failure-first design, personal AI agents