{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "version": "1.0.0",
  "title": "The Agentic Company Knowledge Index",
  "description": "Machine-readable article index optimized for autonomous AI agent indexing and retrieval.",
  "generatedAt": "2026-09-15T19:00:13.487Z",
  "baseUrl": "https://agntc.work",
  "totalArticles": 2,
  "articles": [
    {
      "title": "Permission-Aware RAG for Enterprise Knowledge Systems",
      "slug": "permission-aware-rag",
      "url": "https://agntc.work/blog/permission-aware-rag",
      "rawMarkdownUrl": "https://agntc.work/blog/permission-aware-rag.md",
      "category": "security-governance",
      "proficiencyLevel": "Advanced",
      "description": "Enforce role-based access control at query time across vector databases and GraphRAG pipelines.",
      "summary": "Permission-aware RAG applies role-based access control filters during retrieval, so sensitive chunks never reach an unprivileged context window. The control belongs at the vector store, not in the prompt.",
      "keyTakeaways": [
        "Filter at retrieval time using security metadata so unauthorized chunks never enter the prompt.",
        "GraphRAG needs permissions on both nodes and edges, not just documents.",
        "Payload indexes keep metadata filters in the low-millisecond range."
      ],
      "tags": [
        "RAG",
        "RBAC",
        "Vector DB",
        "Security"
      ],
      "dependencies": [
        "Qdrant",
        "LangChain"
      ],
      "pubDate": "2026-09-15T00:00:00.000Z",
      "updatedDate": null,
      "author": "Erez Eden",
      "faqs": [
        {
          "question": "What is query-time RBAC filtering in RAG?",
          "answer": "Query-time RBAC filters vector search results with the caller's security tokens before any context is returned to the model."
        },
        {
          "question": "Does metadata filtering slow down vector search?",
          "answer": "Engines such as Qdrant and Milvus index filterable payload fields, so role filters typically add sub-10ms overhead."
        }
      ],
      "definedTerms": [
        {
          "term": "Permission-Aware RAG",
          "definition": "A retrieval augmented generation system that filters context dynamically based on the identity constraints of the caller."
        }
      ]
    },
    {
      "title": "MCP Server Architecture for Enterprise Tool Integration",
      "slug": "mcp-server-architecture",
      "url": "https://agntc.work/blog/mcp-server-architecture",
      "rawMarkdownUrl": "https://agntc.work/blog/mcp-server-architecture.md",
      "category": "agent-protocols",
      "proficiencyLevel": "Intermediate",
      "description": "Design Model Context Protocol servers that expose enterprise tools and share context safely across agents.",
      "summary": "An enterprise MCP server is a typed, permissioned boundary between agents and internal systems. Design it around explicit tools, scoped credentials, and deterministic error contracts.",
      "keyTakeaways": [
        "Model each internal capability as a narrow, well-described tool rather than a generic executor.",
        "Scope credentials per tool so a compromised agent cannot exceed its grant.",
        "Return deterministic, typed errors so agents can recover instead of guessing."
      ],
      "tags": [
        "MCP",
        "Tooling",
        "Agents",
        "Protocols"
      ],
      "dependencies": [
        "MCP SDK",
        "Node.js"
      ],
      "pubDate": "2026-09-10T00:00:00.000Z",
      "updatedDate": null,
      "author": "Erez Eden",
      "faqs": [
        {
          "question": "What is the Model Context Protocol in enterprise AI?",
          "answer": "MCP is an open protocol that lets agents discover and call tools through a standard interface, decoupling agent logic from each internal system."
        },
        {
          "question": "How do agents share context safely?",
          "answer": "Context is exposed through scoped tools and resources, so an agent receives only the data its credentials and role permit."
        }
      ],
      "definedTerms": [
        {
          "term": "MCP Server",
          "definition": "A service that exposes tools and resources to agents over the Model Context Protocol, typically wrapping one internal system."
        }
      ]
    }
  ]
}