--- format: "aidr-story-markdown/v1" id: "da92b80397690dde35e85c3960ba478f2843576edc4b235e23bac4e2e0dfbd2c" canonical_url: "https://aidr.today/da92b803?lang=en" title: "Structured Authority Injection: Persistent Human Control for LLM Agents via Typed MCP Overrides" lang: "en" requested_lang: "en" available_langs: ["en","vi"] translation_fallback: null fallback_fields: [] published_at: "2026-10-19T04:00:00.000Z" category: "Frameworks" topics: ["agent","framework"] source_urls: ["https://arxiv.org/abs/2610.22373"] summary: "Structured Authority Injection (SAI) is a protocol that enables human operators to inject binding directives into LLM agents through typed, schema-validated Model Context Protocol (MCP) tool calls, maintaining a ranked authority context prepended to each prompt. SAI defines three override classes—Constraint, Priority, and Strategy—with distinct persistence semantics and an explicit precedence order enforced via a directed authority channel inaccessible to the planning process. The method requires no model fine-tuning or access to model weights and applies to instruction-tuned LLMs supporting MCP tool use." --- # Structured Authority Injection: Persistent Human Control for LLM Agents via Typed MCP Overrides > [Open the canonical story]() **Published:** 2026-10-19T04:00:00.000Z **Category:** Frameworks **Topics:** agent, framework ## Summary Structured Authority Injection \(SAI\) is a protocol that enables human operators to inject binding directives into LLM agents through typed, schema\-validated Model Context Protocol \(MCP\) tool calls, maintaining a ranked authority context prepended to each prompt\. SAI defines three override classes—Constraint, Priority, and Strategy—with distinct persistence semantics and an explicit precedence order enforced via a directed authority channel inaccessible to the planning process\. The method requires no model fine\-tuning or access to model weights and applies to instruction\-tuned LLMs supporting MCP tool use\. ## Sources - [Story source]()