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docs/configuration/holmesgpt/builtin_toolsets.rst

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toolsets/internet
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toolsets/kafka
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toolsets/kubernetes
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toolsets/notion
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toolsets/opensearch_logs
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toolsets/opensearch_status
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toolsets/prometheus
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:class-card: sd-bg-light sd-bg-text-light
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:link: toolsets/kubernetes
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:link-type: doc
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.. grid-item-card:: :octicon:`cpu;1em;` Notion
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:class-card: sd-bg-light sd-bg-text-light
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:link: toolsets/notion
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:link-type: doc
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.. grid-item-card:: :octicon:`cpu;1em;` OpenSearch logs
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:class-card: sd-bg-light sd-bg-text-light

docs/configuration/holmesgpt/index.rst

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builtin_toolsets
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permissions
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custom_toolsets
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remote_mcp_servers
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Why use HolmesGPT?
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^^^^^^^^^^^^^^^^^^^
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Robusta can integrate with `Holmes GPT <https://github.com/robusta-dev/holmesgpt>`_ to analyze health issues on your cluster, and to run AI based root cause analysis for alerts.
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This requires a Robusta SaaS account, and for the Robusta UI sink to be enabled. (We have plans to support HolmesGPT in a pure OSS mode in the near future. Stay tuned!)
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When available, AI based investigations can be launched in one of two ways:
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1. Click the ``Ask HolmesGPT`` button in Slack. The AI investigation will be sent back as a new message.
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1. Choose an AI model - we highly recommend using GPT-4o to get the most accurate results! Other models may work, but are not officially supported.
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2. :ref:`Configure your AI provider with the chosen model <Choosing and configuring an AI provider>`.
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3. :ref:`Optional: Configure HolmesGPT Access to SaaS Data <Configuring HolmesGPT Access to SaaS Data>`.
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3. :ref:`Configure HolmesGPT Access to SaaS Data <Configuring HolmesGPT Access to SaaS Data>`.
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Choosing and configuring an AI provider
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----------------------------------------
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Custom toolsets are created through your Helm values file and you can find instructions
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to :doc:`write your own toolsets here <builtin_toolsets>`.
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Remote MCP servers
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---------------------
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.. warning::
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Remote MCP servers are in **Tech Preview** stage.
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Remote MCP server connections are configured through your Helm values file.
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For detailed instructions, refer to the :doc:`Connecting to Remote MCP Servers <remote_mcp_servers>` guide.
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Remote MCP Servers
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====================
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.. warning::
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Remote MCP servers are in **Tech Preview** stage.
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HolmesGPT can integrate with remote MCP servers using SSE mode.
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This capability enables HolmesGPT to access external data sources and tools in real time.
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This guide provides step-by-step instructions for configuring HolmesGPT to connect with remote MCP servers over SSE.
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Example : MCP server configuration
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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.. md-tab-set::
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.. md-tab-item:: Robusta Helm Chart
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**Helm Values:**
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.. code-block:: yaml
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holmes:
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mcp_servers:
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mcp_server_1:
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# human-readable description of the mcp server (this is not seen by the AI model - its just for users)
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description: "Remote mcp server"
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url: "http://example.com:8000/sse"
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mcp_server_2:
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description: "MCP server that runs in my cluster"
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url: "http://<service-name>.<namespace>.svc.cluster.local:<service-port>"
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config:
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headers:
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key: "{{ env.my_mcp_server_key }}" # You can use holmes environment variables as headers for the MCP server requests.
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Update your Helm values with the provided YAML configuration, then apply the changes with Helm upgrade:
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.. code-block:: bash
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helm upgrade robusta robusta/robusta --values=generated_values.yaml --set clusterName=<YOUR_CLUSTER_NAME>
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helm/robusta/values.yaml

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# parameters for the robusta forwarder deployment
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kubewatch:
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image: ~ # image can be used to override image.registry/imageName
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imageName: kubewatch:v2.9.0
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imageName: kubewatch:v2.11.0
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imagePullPolicy: IfNotPresent
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pprof: True
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resources:

src/robusta/integrations/jira/client.py

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issue = issues.get("issues")[0]
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if issues.get("total", 0) > 1:
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logging.warn(f"More than one issue found for query: '{query}', picking most recent one")
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logging.warning(f"More than one issue found for query: '{query}', picking most recent one")
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logging.debug(f"Picked issue '{issue}'")
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return issue

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