Microsoft has released a public preview that enables Azure Logic Apps (Standard) to run as Model Context Protocol (MCP) servers, exposing Logic Apps workflows as agent tools discoverable and callable by MCP-capable clients (e.g., VS Code + Copilot).
What’s actually shipping
- Remote MCP server on Logic Apps (Standard): You configure a Standard logic app to host an MCP endpoint (
/api/mcp) and surface HTTP Request/Response workflows as tools. Authentication is front-doored by Easy Auth; MCP endpoints default to OAuth 2.0. VS Code (≥1.102) includes GA MCP client support for testing. - API Center registration path (preview): You can also create/register MCP servers in Azure API Center, where selected managed connector actions become tools with cataloging and governance.
Key requirements and transport details
- Workflow shape: Tools must be implemented as HTTP Request trigger (“When a HTTP request is received”) plus a Response action.
- Auth & access control: By default, MCP uses OAuth 2.0; Easy Auth enforces client/identity/tenant restrictions. During setup, App Service authentication must allow unauthenticated requests (the MCP flow still performs OAuth).
- Transports: Streamable HTTP works out of the box. SSE additionally requires VNET integration and
host.jsonsettingRuntime.Backend.EdgeWorkflowRuntimeTriggerListener.AllowCrossWorkerCommunication=true. - Enablement switch: MCP APIs are enabled by adding
extensions.workflow.McpServerEndpoints.enable=truein host.json.
API Center path: preview limitations that matter
When creating MCP servers via API Center backed by Logic Apps, the current preview imposes the following limits:
- Start with an empty Standard logic app resource.
- One connector per MCP server.
- Built-in service-provider and custom connectors aren’t supported in this path (managed connectors only).
- One action per tool.
These constraints materially affect tool granularity and server layout in larger estates.
Why Standard (single-tenant) is the target?
Standard runs on the single-tenant Logic Apps runtime (on Azure Functions), supports multiple workflows per app, and integrates directly with virtual networks and private endpoints—all relevant for exposing private systems safely to agents and for predictable throughput/latency. By contrast, Consumption is multitenant, single-workflow per app, and pay-per-execution.
Tooling semantics and discoverability
Microsoft recommends adding trigger descriptions, parameter schemas/descriptions, and required markers to improve agent tool selection and invocation reliability. These annotations are read by MCP clients and influence calling behavior.
Connectors and enterprise reach
Organizations can front existing workflows and a large catalog of Logic Apps connectors (cloud and on-prem) through MCP, turning them into callable agent tools; Microsoft explicitly cites “more than 1,400 connectors.”
Operations, governance, and testing
Run history plus Application Insights/Log Analytics are available for diagnostics and auditability. VS Code provides quick client validation via MCP: Add Server, including OAuth sign-in and tool enumeration. Registering via API Center brings discovery/governance to MCP servers across teams.
Production notes (preview)
- SSE requires both VNET and the cross-worker setting; without these, use streamable HTTP.
- Easy Auth must be configured precisely (including the “allow unauthenticated” toggle) or client sign-in flows will fail despite OAuth expectations.
- Throttling, idempotency, and schema versioning remain your responsibility when wrapping connectors as tools (not new, but now in the agent path). InfoQ highlights similar operational concerns from early adopters.
Summary
The preview cleanly MCP-enables Logic Apps (Standard): you expose HTTP-based workflows as OAuth-protected tools; you can catalog them in API Center; and you can reach private systems through single-tenant networking. For teams already invested in Logic Apps, this is a low-friction, standards-aligned route to operationalize enterprise agent tooling—just mind the API Center limits, SSE prerequisites, and Easy Auth nuances during rollout.
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Michal Sutter is a data science professional with a Master of Science in Data Science from the University of Padova. With a solid foundation in statistical analysis, machine learning, and data engineering, Michal excels at transforming complex datasets into actionable insights.
