Post a weekly reliability report with AI

This guide builds a report that writes itself every Monday. The workflow collects the past week’s numbers from your KloudMate workspace, and an AI Prompt step turns them into a short report for the engineering channel: the busiest services and their error rates, the incidents that are still open, and the SLOs that are running out of error budget.

The numbers come from the KloudMate MCP server, the same server that coding tools such as Claude Code use to query KloudMate. A workflow connects to it as a Custom MCP Server, and MCP Tool Call steps call its tools the way an agent would. Each step calls one tool that you pick, with the arguments you set, so the workflow asks the same questions every week.

The finished workflow has these steps:

Schedule: Mondays at 09:00
├─ Collect the week's data             Parallel
│  ├─ Requests and latency by service  MCP Tool Call
│  ├─ Errors by service                MCP Tool Call
│  ├─ Open incidents                   MCP Tool Call
│  └─ SLOs                             MCP Tool Call
├─ Write the report                    AI Prompt
└─ Post the report                     Slack: Post Message

Before you start

• You need the Developer role in a KloudMate workspace whose plan includes workflows.
• You need a Slack connection with the Workflows capability, and a channel for the report. Invite the KloudMate bot to that channel.
• Each run uses workflow credits, and the AI Prompt step uses more. See Check workflow usage.

Step 1: Connect the KloudMate MCP server

1. Create a personal API key and copy it. The workflow reads whatever the key’s owner can read, so create it from an account that can see every service you want in the report.

2. Copy the ID of this workspace from its URL in the KloudMate app. It starts with ws_.

3. Open Workflows → Connections, click Connect, and pick Custom MCP Server. Name the connection KloudMate MCP, and fill in the form:

   Field	Value
   Server URL	https://api.kloudmate.com/mcp
   Transport	Streamable HTTP
   Authentication	Bearer token, with your personal API key as the token
   Extra headers	{"x-workspace-id": "YOUR_WORKSPACE_ID"}

4. Click Connect.

The personal key works for every workspace its owner belongs to, and x-workspace-id picks the one the tools read. KloudMate stores the key encrypted with the connection, so it never appears in the workflow or in run history.

Step 2: Import the workflow

1. Copy the YAML below.
2. Open Workflows, click Import, paste the YAML, and click Import.
3. Click Open workflow, and set these before you publish:
   • On the four MCP Tool Call steps, pick your KloudMate MCP connection.
   • On Post the report, pick your Slack connection and the channel.
   • On the trigger, set Timezone to your team’s timezone, such as Europe/Berlin.

kind: workflow
uid: guide-weekly-reliability-report
spec:
  name: Weekly reliability report
  description: Every Monday, reads the past week's traffic, errors, open incidents, and SLOs from the KloudMate MCP server, and posts a report that AI writes from them.
  definition:
    schema_version: 1
    trigger:
      type: schedule
      config:
        mode: weekly
        weekday: 1
        hour: 9
        minute: 0
        timezone: UTC
    steps:
      - id: collect
        type: parallel
        display_name: Collect the week's data
        branches:
          - - id: traffic
              type: action
              action: mcp.call
              display_name: Requests and latency by service
              connection_id:
                $input: kloudmate_mcp
              with:
                tool: get_service_requests_count_and_avg_latency
                arguments:
                  from: now-7d
                  to: now
          - - id: errors
              type: action
              action: mcp.call
              display_name: Errors by service
              connection_id:
                $input: kloudmate_mcp
              with:
                tool: get_service_error_count
                arguments:
                  from: now-7d
                  to: now
          - - id: incidents
              type: action
              action: mcp.call
              display_name: Open incidents
              connection_id:
                $input: kloudmate_mcp
              with:
                tool: search_incidents
                arguments:
                  limit: 50
          - - id: slos
              type: action
              action: mcp.call
              display_name: SLOs
              connection_id:
                $input: kloudmate_mcp
              with:
                tool: search_slos
                arguments:
                  enabled: true
                  limit: 50
      - id: write
        type: action
        action: ai.prompt
        display_name: Write the report
        with:
          prompt: |-
            Write this week's reliability report for the engineering team, as a Slack message. Use Slack formatting: *bold* for headings and short bullet lists. Keep it under 250 words, and don't include links.

            Include these sections:
            1. Traffic and errors: the five busiest services, with their request count and error rate. Error rate is the service's errors divided by its requests, as a percentage.
            2. Open incidents: how many are open, and the three highest-severity ones by title.
            3. SLOs at risk: every SLO that is breached or has less than 25% of its error budget left.

            Use only the numbers in the data below. If a section has no data, say so in one line. Latency in the data is in nanoseconds, so show it in milliseconds.

            Requests and average latency by service:
            {{ steps.traffic.output.result }}

            Errors by service:
            {{ steps.errors.output.result }}

            Open incidents:
            {{ steps.incidents.output.result }}

            SLOs:
            {{ steps.slos.output.result }}
      - id: post
        type: action
        action: slack.post_message
        display_name: Post the report
        connection_id:
          $input: slack
        with:
          text: "{{ steps.write.output.text | replace: '<!', '&lt;!' }}"
inputs:
  kloudmate_mcp:
    kind: connection
    name: KloudMate MCP
    type: custom_mcp
  slack:
    kind: connection
    name: Slack
    type: slack

How each step works

Collect the week’s data

A Parallel step runs four MCP Tool Call steps at the same time, one in each branch. Each step calls one tool on the KloudMate MCP server:

Step	Tool	Arguments
Requests and latency by service	get_service_requests_count_and_avg_latency	from is now-7d, and to is now
Errors by service	get_service_error_count	from is now-7d, and to is now
Open incidents	search_incidents	limit is 50
SLOs	search_slos	enabled is true, and limit is 50

Pick the tool from the Tool list, and the step builds the Arguments form from the tool’s own input schema. The tools accept a relative time such as now-7d, so the same step reads the last seven days every week. search_incidents returns the incidents that aren’t resolved yet, and search_slos returns each SLO with its latest compliance and error budget.

Every tool on this server only reads data, so the workflow can’t change anything in KloudMate. Each step returns what the tool answered as result, so the next step reads it as {{ steps.errors.output.result }}. See MCP Tool Call.

Write the report

An AI Prompt step writes the report. The Prompt gives the model the structure to follow and the rules for the numbers, and then the data from the four tools:

Requests and average latency by service:
{{ steps.traffic.output.result }}

Errors by service:
{{ steps.errors.output.result }}

When a reference sits inside other text, an object or a list renders as JSON, which the model reads well. So the prompt doesn’t depend on the exact shape each tool returns, and the model does the arithmetic, such as each service’s error rate.

The prompt asks the model to use only numbers from the data, and to say so when a section has none, which keeps it from filling a gap with a guess. Read the first few reports against the numbers in KloudMate before you rely on them.

AI Prompt fits here because the data comes from your own workspace. Incident titles and service names are written by your team and your systems. When a prompt includes text that someone outside your team can write, such as a support ticket or a Slack message, use AI Extract instead, which can’t return anything outside its output fields. See AI Prompt.

Post the report

A Slack Post Message step posts steps.write.output.text. The replace filter turns <! into <!, which stops text such as <!channel> from notifying the whole channel if the model ever writes it:

{{ steps.write.output.text | replace: '<!', '&lt;!' }}

Step 3: Test and publish

1. Test each of the four MCP Tool Call steps from its Test tab. The output shows what the tool returned for your workspace, and a connection problem shows up here first.
2. Click Test run. It writes a report from this week’s data and posts it in the channel.
3. Compare the report with what KloudMate shows for the same week, and adjust the prompt if you want a different focus.
4. Click Publish. The first publish also switches the workflow on.

Adapt the workflow

• Report on other data. Add another MCP Tool Call step to Collect the week’s data, such as search_alert_states for the alerts firing now. Then add its result to the prompt, with a line that says what it is. The KloudMate MCP server page lists the tools.
• Report every day. Change the trigger to Daily, and change now-7d to now-1d in the arguments.
• Email the report instead. Replace Post the report with a Send Email step, and ask for Markdown instead of Slack formatting in the prompt, because Send Email reads Markdown.
• Use another MCP server. An MCP Tool Call step can call any server you connect as a Custom MCP Server, such as an internal service your team built. Use API key in a header under Authentication for a server that wants its key in a named header.

Related

• MCP Tool Call for the step’s fields and output.
• KloudMate MCP Server for the server’s tools and connection details.
• Connections for Custom MCP Server connections.