This week’s update focuses on the Model Context Protocol (MCP) as the enterprise standard, headlined by the launch of the Power BI Modeling MCP Server in public preview — enabling AI agents to autonomously, securely, and manage Power BI semantic models via bulk operations.
Agent orchestration matured significantly with Microsoft Foundry unifying frameworks to support hierarchical coordination, allowing a Coordinator agent to delegate complex, fault-tolerant tasks to specialized child agents.
The MCP ecosystem rapidly expanded as new servers from Devolutions (RDM) and Unthread launched to secure privileged access management and simplify conversational operations — while a demonstration confirmed that the assistant from AnthropicAI can use MCP for secure, local Windows file integration.
Research introduced sophisticated agent frameworks — Agent‑R1, Octopus, and Orion — pushing the boundaries of multimodal and tool-based reasoning. On the flip side, the Cloudflare outage served as a reminder that system resilience and safety mechanisms — core tenets of MCP standards — remain critical for continuous enterprise operations.
Major Updates of the Week
Power BI Modeling MCP Server Launch
- Microsoft launched the Power BI Modeling MCP Server in public preview. This server implements MCP to securely connect AI agents directly to Power BI semantic models.
- It enables comprehensive model management: agents can create, update, and delete key components like Tables, Columns, Measures (DAX), Relationships, Roles, and Object-Level Security (OLS). The support spans across Power BI Desktop, Fabric Workspaces, and PBIP files.
- The server is built for scale: it supports bulk modeling operations (e.g., refactoring or applying security rules) on hundreds of objects simultaneously, with transaction support to ensure model consistency.
- Validation and safety mechanisms are baked in via the Elicitation MCP protocol — requiring user approval before first modification or query against a semantic model; agents can also execute and validate DAX queries.
- Because the server proxies requests to Power BI, users are strongly advised to backup models before performing operations — unintended changes from LLM-driven modifications are possible.
Agent Runtimes & Orchestration Systems
Microsoft Foundry: Hierarchical Agent Coordination
- In a recent session at Microsoft Ignite, Foundry was presented as a unified agent framework merging strengths of existing frameworks (e.g. AutoGen, Semantic Kernel).
- It creates a foundation for both non-deterministic agents (LLM + tools + memory) and deterministic workflows, integrating standards like MCP (for context retrieval) and A2A (for inter-agent chat).
- Key features include hierarchical execution: a Coordinator agent can delegate large or long-running tasks to specialized child agents — enabling modular, manageable, and scalable executions.
- Shared memory ensures seamless context propagation and state tracking between agents.
- Fault tolerance is supported via durable task extensions, enabling long-running operations with planned human-in-the-loop pauses as needed.
Devolutions RDM: Secure Privileged Access Management
- Devolutions released a Remote Desktop Manager (RDM) MCP Server, creating a secure automation layer that enables AI assistants to interact with RDM without exposing credentials.
- The server enforces mandatory user approval workflows, credential isolation, and full audit logging for every AI-powered action.
- It uses a secure, user-scoped named-pipe transport — designed as a more secure isolation layer than standard localhost HTTP, suitable for high-trust environments.
- It supports multiple LLM backends, including OpenAI, Google Gemini, Anthropic, as well as self-hosted options.
Unthread: Conversational Interface for Operations
- Unthread launched an MCP Server aimed at simplifying AI integration for support and operations teams.
- The server’s functionality allows connecting various platforms — ticketing systems, HR tools, internal operations — through a single conversational interface.
- Teams can trigger workflow actions directly via chat (e.g., via ChatGPT or Claude), significantly reducing repetitive tickets and improving response times.
- Early adoption reports (e.g., from partner Lemonade) highlight faster operations and faster feature delivery.
MCP Use Case: Local Windows Integration
- A demo by a Windows developer showed that Claude (from AnthropicAI) can leverage MCP on Windows to simplify everyday tasks — such as summarizing documents in the Downloads folder or organizing project files — via natural-language commands.
- The design ensures user consent gating (particularly before accessing file explorer), preserving endpoint security while enabling smooth workflows.
Cloudflare’s Rough Week: A Reminder on Keeping Things Running
- On November 18, Cloudflare experienced a service outage for a couple of hours. The disruption impacted many websites and business tools.
- The root cause was a misconfiguration in their bot-blocking setup that caused a massive config file to crash the system.
- This incident underscores the importance of infrastructure resilience: for those building with MCP, the ability for agents to maintain continuity and safely resume operations after an unexpected system failure — a core focus of MCP standards — is more valuable than pure speed.
Community Debugging, Issues, and Solutions
Power BI MCP Server Deployment Fix
- A community discussion (on Reddit) about the official Power BI Modeling MCP Server revealed an initial deployment hurdle: a tenant authentication error prevented connection to semantic models within Fabric Workspaces.
- Further concerns included limitations related to interacting with report visuals, which affects operations like cleaning up unused measures, and broader governance/trust concerns due to potential LLM-driven errors in production.
- Workarounds in the community included ensuring human validation of changes and relying on Git / TMDL version control for auditing and safety.
Agent Sandbox File Access Workaround
- On the Cursor forum, users reported missing file access when running tools (e.g. database migration scripts) within isolated Agent Sandbox environments.
- The suggested workaround: include
.envfiles in the sandbox mounts so database migration tools have the necessary configuration and environment variables to function correctly within the isolated environment.
My Thoughts: Beyond the Hype Cycle
The notion that MCP is overhyped or dying overlooks the fundamental needs of enterprise adoption. The strategic significance of this week’s announcements — especially Microsoft launching the official Power BI Modeling MCP Server with transactional support and mandatory security features, and Devolutions using MCP for secure, high-trust privileged access management — is strong evidence that MCP is not a fad. Rather, it is becoming an operational necessity when building AI systems at enterprise scale.
Laboratory-grade autonomous agents are interesting, but for real-world, mission-critical enterprise systems, standardized context, isolation, and auditability provided by MCP are non-negotiable. Ignoring MCP now means staying locked into proof-of-concept mode — unable to scale agents into secure, production-grade workflows. MCP is emerging as the de facto “API of Trust” required to bridge agents with real business systems.
About the author: Technical Evangelist at Gentoro
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