Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@RE-Butler MCP Server search for requirements on authentication"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Outbound MCP server exposing RE-Butler's knowledge and validation tools to neighbour teams and Azure AI Foundry agents.
Tool | Auth | Description |
| RE.Read | Hybrid semantic search over LLM Wiki |
| RE.Read | List available knowledge domains |
| RE.Read | Get User Story / EARS / Gherkin templates |
| RE.Read | Fetch a specific wiki page |
| RE.Read | INVEST/QUS/EARS validation |
| RE.Admin | Create ADO work item (HITL Gate C) |
Related MCP server: Azure DevOps MCP Server
pip install -e ".[dev]"
cp .env.example .env # fill in values
python -m re_butler_mcp.serverpytest# Against local server
python scripts/smoke_test_client.py
# Against deployed server
python scripts/smoke_test_client.py https://ca-genai4re-mcp-dev.<region>.azurecontainerapps.io/mcpcd infra
az deployment group create \
--resource-group rg-genai4re-dev \
--template-file main.bicep \
--parameters containerImage=myacr.azurecr.io/re-butler-mcp:latest acrName=myacrCallers must present a valid Entra ID Bearer JWT.
App Roles: RE.Read (all reads), RE.Admin (write tools).
Pre-authorize client app registrations in the server's app registration manifest.
Managed Identity handles all outbound calls (Search, OpenAI, ADO).
create_work_item always returns approval_pending: true. The calling workflow (Foundry / Durable Functions) must implement the approval step before the work item becomes active. Do not implement Gate C inside Connected Agent tools — keep it in the workflow layer.
This server cannot be deployed
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