/microsoft-foundry

Tool — Remote MCP server, no auth (type: mcp)

Attach a public remote MCP server (no credentials) to a toolbox. A no-auth server still needs a connection (--kind remote-tool --auth-type none) — the toolbox references it by name and the created toolbox tool carries a populated project_connection_id.

🚦 Before creating a toolbox/connection either way, read create-hosted.md → Toolbox creation boundary.

A. Imperative CLI

Steps 1–3 of toolbox.md § The flow. Write the toolbox spec to a file — azd ai toolbox create --from-file takes a path (stdin - is not supported).

# 0. Install the CLI extension (once)
azd extension install azure.ai.toolboxes

# 1. Create the no-auth connection
azd ai connection create learn-mcp-conn \
  --kind remote-tool --target https://learn.microsoft.com/api/mcp \
  --auth-type none --project-endpoint "$FOUNDRY_PROJECT_ENDPOINT"

# Write the toolbox spec to a file
cat > learn-mcp.yaml <<'EOF'
description: learn-mcp toolbox
connections:
  - name: learn-mcp-conn
EOF

Create a new toolbox (first version auto-promoted):

azd ai toolbox create learn-tools --from-file learn-mcp.yaml --project-endpoint "$FOUNDRY_PROJECT_ENDPOINT"

azd ai toolbox create / delete require an azd environment (run inside an azd init'd directory), unlike connection create / toolbox show which work with just --project-endpoint.

Add to an existing toolbox (new version — then promote):

azd ai toolbox connection add learn-tools learn-mcp-conn --project-endpoint "$FOUNDRY_PROJECT_ENDPOINT"
azd ai toolbox publish learn-tools <new-version> --project-endpoint "$FOUNDRY_PROJECT_ENDPOINT"

connection add creates a new immutable version but leaves the default unchanged until you publish it.

--from-file entry:

connections:
  - name: learn-mcp-conn       # RemoteTool — just the name; project_connection_id is populated

B. Declarative azure.yaml

Declare the toolbox as a host: azure.ai.toolbox service in azure.yaml; azd deploy upserts it (and auto-promotes the new version). A no-auth MCP server is declared under tools: with an inline server_url — no connection needed on this path.

name: my-agent-project
services:
  agent-tools:
    host: azure.ai.toolbox
    description: learn-mcp toolbox
    tools:
      - type: mcp
        server_label: learn_mcp
        server_url: https://learn.microsoft.com/api/mcp
        require_approval: never

  # A hosted agent in the same project consumes the toolbox by name
  my-agent:
    host: azure.ai.agent
    uses:
      - agent-tools          # depend on the toolbox service
    environmentVariables:
      - name: TOOLBOX_NAME
        value: agent-tools    # agent resolves the MCP endpoint at runtime

azd deploy agent-tools

Requirements & gotchas:

• Set FOUNDRY_PROJECT_ENDPOINT and AZURE_SUBSCRIPTION_ID in the azd env (after it's created) before azd deploy, or it errors infrastructure has not been provisioned. No azd provision / infra: block is needed.

The agent references the toolbox by name (TOOLBOX_NAME), so the MCP endpoint resolves at runtime — no endpoint string is hard-coded. See use-toolbox-in-hosted-agent.md.

Verify & deploy

After creating the toolbox either way, verify its MCP endpoint end-to-end (bearer token + raw tools/list / tools/call) — see test-endpoint.md.

References

• Microsoft Learn MCP server — the public example used above
• MCP tool documentation
• toolbox.md § Supported tool types