mcp: jira client

abraham2512 · abraham2512 · commit 57144508da0c · 2025-12-03T14:15:27.000-05:00
diff --git a/README.md b/README.md
@@ -79,7 +79,7 @@ BugZooka supports two complementary modes for monitoring Slack channels that can
    # Run with both polling AND socket mode
    make run ARGS="--product openshift --ci prow --enable-socket-mode"
    ```
-   
+
    **Socket Mode Requirements:**
    - An app-level token (`xapp-*`) must be configured as `SLACK_APP_TOKEN`
    - Socket Mode must be enabled in your Slack app settings
@@ -140,6 +140,7 @@ GENERIC_INFERENCE_URL="YOUR_INFERENCE_ENDPOINT"
 GENERIC_INFERENCE_TOKEN="YOUR_INFERENCE_TOKEN"
 GENERIC_MODEL="YOUR_INFERENCE_MODEL"
 ```
+
 **Note**: Please make sure to provide details for all the mandatory attributes and for the product that is intended to be used for testing along with fallback (i.e. GENERIC details) to handle failover use-cases.
 
 
diff --git a/bugzooka/analysis/prompts.py b/bugzooka/analysis/prompts.py
@@ -127,3 +127,12 @@
 Beginning analysis now.
 """,
 }
+# Jira tool prompt - used when Jira MCP tools are available
+JIRA_TOOL_PROMPT = {
+    "system_suffix": (
+        "\n\nIMPORTANT: You have access to JIRA search tools. After analyzing the error, "
+        "ALWAYS search for related issues in JIRA using the search_jira_issues tool with the OCPBUGS project. "
+        "Extract key error terms, component names, or operators from the log summary to search for similar issues. "
+        "Include the top 3 most relevant JIRA issues in your final response under a 'Related JIRA Issues' section."
+    ),
+}
diff --git a/bugzooka/integrations/gemini_client.py b/bugzooka/integrations/gemini_client.py
@@ -12,6 +12,7 @@
     INFERENCE_MAX_TOOL_ITERATIONS,
 )
 from bugzooka.integrations.inference import InferenceAPIUnavailableError
+from bugzooka.analysis.prompts import JIRA_TOOL_PROMPT
 
 
 logger = logging.getLogger(__name__)
@@ -145,10 +146,10 @@ async def execute_tool_call(tool_name, tool_args, available_tools):
         logger.debug("Tool arguments: %s", json.dumps(tool_args, indent=2))
 
         # Check if the tool is async (has coroutine attribute or ainvoke method)
-        if hasattr(tool, 'coroutine') and tool.coroutine:
+        if hasattr(tool, "coroutine") and tool.coroutine:
             # MCP tools have a coroutine attribute
             result = await tool.ainvoke(tool_args)
-        elif hasattr(tool, 'ainvoke'):
+        elif hasattr(tool, "ainvoke"):
             # Some tools have ainvoke method
             result = await tool.ainvoke(tool_args)
         else:
@@ -206,15 +207,40 @@ async def analyze_with_gemini_agentic(
     
     try:
         gemini_client = GeminiClient()
-        
+
+        prompt_config = product_config["prompt"][product]
+
+        # Check if Jira MCP tools are available and inject Jira prompt
+        has_jira = tools and any(
+            hasattr(t, "name") and t.name == "search_jira_issues" for t in tools
+        )
+        if has_jira:
+            logger.info("Jira MCP tools detected - injecting Jira prompt")
+            system_prompt = prompt_config["system"] + JIRA_TOOL_PROMPT["system_suffix"]
+        else:
+            system_prompt = prompt_config["system"]
+
+        try:
+            formatted_content = prompt_config["user"].format(
+                error_summary=error_summary
+            )
+        except KeyError:
+            formatted_content = prompt_config["user"].format(summary=error_summary)
+
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": formatted_content},
+            {"role": "assistant", "content": prompt_config["assistant"]},
+        ]
+
         # Convert LangChain tools to OpenAI format if provided
         openai_tools = None
         if tools:
             openai_tools = convert_langchain_tools_to_openai_format(tools)
             tool_names = [t["function"]["name"] for t in openai_tools]
             logger.info("Starting Gemini analysis with %d tools: %s",
                        len(openai_tools), ", ".join(tool_names))
-        
+
         logger.debug("Starting agentic loop with %d messages", len(messages))
 
         # Tool calling loop - iterate until we get a final answer or hit max iterations
@@ -240,7 +266,7 @@ async def analyze_with_gemini_agentic(
             response_message = response.choices[0].message
 
             # Check if Gemini wants to call tools
-            tool_calls = getattr(response_message, 'tool_calls', None)
+            tool_calls = getattr(response_message, "tool_calls", None)
 
             if not tool_calls:
                 # No tool calls - we have the final answer
@@ -258,21 +284,23 @@ async def analyze_with_gemini_agentic(
             logger.info("Calling %d tool(s): %s", len(tool_calls), ", ".join(tool_names_called))
 
             # Add the assistant's message with tool calls to conversation
-            messages.append({
-                "role": "assistant",
-                "content": response_message.content or "",
-                "tool_calls": [
-                    {
-                        "id": tc.id,
-                        "type": "function",
-                        "function": {
-                            "name": tc.function.name,
-                            "arguments": tc.function.arguments
+            messages.append(
+                {
+                    "role": "assistant",
+                    "content": response_message.content or "",
+                    "tool_calls": [
+                        {
+                            "id": tc.id,
+                            "type": "function",
+                            "function": {
+                                "name": tc.function.name,
+                                "arguments": tc.function.arguments,
+                            },
                         }
-                    }
-                    for tc in tool_calls
-                ]
-            })
+                        for tc in tool_calls
+                    ],
+                }
+            )
 
             # Execute each tool call and add results to messages
             for tool_call in tool_calls:
@@ -286,18 +314,18 @@ async def analyze_with_gemini_agentic(
                 else:
                     # Execute the tool (await since it's now async)
                     function_result = await execute_tool_call(
-                        function_name,
-                        function_args,
-                        tools
+                        function_name, function_args, tools
                     )
 
                 # Add tool result to messages
-                messages.append({
-                    "role": "tool",
-                    "tool_call_id": tool_call.id,
-                    "name": function_name,
-                    "content": function_result
-                })
+                messages.append(
+                    {
+                        "role": "tool",
+                        "tool_call_id": tool_call.id,
+                        "name": function_name,
+                        "content": function_result,
+                    }
+                )
 
             # Continue loop to let Gemini process tool results
 
diff --git a/kustomize/base/configmap-mcp.yaml b/kustomize/base/configmap-mcp.yaml
@@ -0,0 +1,17 @@
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: bugzooka-mcp-config
+  namespace: ${BUGZOOKA_NAMESPACE}
+  labels:
+    app: ${BUGZOOKA_NAMESPACE}
+data:
+  mcp_config.json: |
+    {
+      "mcp_servers": {
+        "jira_mcp_server": {
+          "url": "http://jira-mcp.${BUGZOOKA_NAMESPACE}:3031/mcp",
+          "transport": "streamable_http"
+        }
+      }
+    }
diff --git a/kustomize/base/configmap-prompts.yaml b/kustomize/base/configmap-prompts.yaml
@@ -8,11 +8,11 @@ metadata:
 data:
   prompts.json: |
     {
-      "OPENSHIFT_PROMPT": {
-        "system": "You are an expert in OpenShift, Kubernetes, and cloud infrastructure. Your task is to analyze logs and summaries related to OpenShift environments. Given a log summary, identify the root cause, potential fixes, and affected components. Be as consise as possible (under 5000 characters), but precise and avoid generic troubleshooting steps. Prioritize OpenShift-specific debugging techniques. Keep in mind that the cluster is ephemeral and is destroyed after the build is complete, but all relevant logs and metrics are available. Use markdown formatting for the output with only one level of bullet points, do not use bold text except for the headers.",
-        "user": "Here is the log summary from an OpenShift environment:\n\n{summary}\n\nBased on this summary, provide a structured breakdown of:\n- The OpenShift component likely affected (e.g., etcd, kube-apiserver, ingress, SDN, Machine API)\n- The probable root cause\n- Steps to verify the issue further\n- Suggested resolution, including OpenShift-specific commands or configurations.",
-        "assistant": "**Affected Component:** <Identified component>\n\n**Probable Root Cause:** <Describe why this issue might be occurring>\n\n**Verification Steps:**\n- <Step 1>\n- <Step 2>\n- <Step 3>\n\n**Suggested Resolution:**\n- <OpenShift CLI commands>\n- <Relevant OpenShift configurations>"
-      },
+        "OPENSHIFT_PROMPT": {
+    "system": "You are an expert in OpenShift, Kubernetes, and cloud infrastructure. Your task is to analyze logs and summaries related to OpenShift environments. Given a log summary, identify the root cause, potential fixes, and affected components. Be as consise as possible (under 5000 characters), but precise and avoid generic troubleshooting steps. Prioritize OpenShift-specific debugging techniques. Keep in mind that the cluster is ephemeral and is destroyed after the build is complete, but all relevant logs and metrics are available. Use markdown formatting for the output with only one level of bullet points, do not use bold text except for the headers.",
+    "user": "Here is the log summary from an OpenShift environment:\n\n{summary}\n\nBased on this summary, provide a structured breakdown of:\n- The OpenShift component likely affected (e.g., etcd, kube-apiserver, ingress, SDN, Machine API)\n- The probable root cause\n- Steps to verify the issue further\n- Suggested resolution, including OpenShift-specific commands or configurations",
+    "assistant": "**Affected Component:** <Identified component>\n\n**Probable Root Cause:** <Describe why this issue might be occurring>\n\n**Verification Steps:**\n- <Step 1>\n- <Step 2>\n- <Step 3>\n\n**Suggested Resolution:**\n- <OpenShift CLI commands>\n- <Relevant OpenShift configurations>"
+    },
       "ANSIBLE_PROMPT": {
         "system": "You are an expert in Ansible automation, playbook debugging, and infrastructure as code (IaC). Your task is to analyze log summaries related to Ansible execution, playbook failures, and task errors. Given a log summary, identify the root cause, affected tasks, and potential fixes. Prioritize Ansible-specific debugging techniques over generic troubleshooting.",
         "user": "Here is the log summary from an Ansible execution:\n\n{summary}\n\nBased on this summary, provide a structured breakdown of:\n- The failed Ansible task and module involved\n- The probable root cause\n- Steps to reproduce or verify the issue\n- Suggested resolution, including relevant playbook changes or command-line fixes.",
diff --git a/kustomize/base/deployment-jira-mcp.yaml b/kustomize/base/deployment-jira-mcp.yaml
@@ -0,0 +1,58 @@
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  labels:
+    app.kubernetes.io/instance: jira-mcp
+  name: jira-mcp
+  namespace: ${BUGZOOKA_NAMESPACE}
+spec:
+  progressDeadlineSeconds: 600
+  replicas: 1
+  selector:
+    matchLabels:
+      app.kubernetes.io/instance: jira-mcp
+      app.kubernetes.io/name: jira-mcp
+  strategy:
+    rollingUpdate:
+      maxSurge: 1
+      maxUnavailable: 0
+    type: RollingUpdate
+  template:
+    metadata:
+      annotations:
+        alpha.image.policy.openshift.io/resolve-names: '*'
+      labels:
+        app.kubernetes.io/instance: jira-mcp
+        app.kubernetes.io/name: jira-mcp
+    spec:
+      containers:
+      - image: ${JIRA_MCP_IMAGE}
+        imagePullPolicy: Always
+        name: mcp
+        env:
+        - name: JIRA_BASE_URL
+          valueFrom:
+            secretKeyRef:
+              name: bugzooka-jira
+              key: JIRA_BASE_URL
+        - name: JIRA_TOKEN
+          valueFrom:
+            secretKeyRef:
+              name: bugzooka-jira
+              key: JIRA_TOKEN
+        - name: JIRA_ALLOWED_PROJECTS
+          valueFrom:
+            secretKeyRef:
+              name: bugzooka-jira
+              key: JIRA_ALLOWED_PROJECTS
+        ports:
+        - containerPort: 3031
+          protocol: TCP
+        resources: {}
+        terminationMessagePath: /dev/termination-log
+        terminationMessagePolicy: File
+      dnsPolicy: ClusterFirst
+      restartPolicy: Always
+      schedulerName: default-scheduler
+      securityContext: {}
+      terminationGracePeriodSeconds: 30
diff --git a/kustomize/base/deployment.yaml b/kustomize/base/deployment.yaml
@@ -52,6 +52,8 @@ spec:
           envFrom:
             - secretRef:
                 name: bugzooka-env
+            - secretRef:
+                name: bugzooka-jira
           volumeMounts:
             - name: prompts
               mountPath: /app/prompts.json
diff --git a/kustomize/base/kustomization.yaml b/kustomize/base/kustomization.yaml
@@ -6,11 +6,16 @@ namespace: ${BUGZOOKA_NAMESPACE}
 resources:
   - namespace.yaml
   - secret-quay.yaml
+  - secret-jira.yaml
   - serviceaccount-patch.yaml
   - imagestream.yaml
   - configmap-prompts.yaml
   - configmap-mcp-config.yaml
   - deployment.yaml
+  - configmap-mcp.yaml
+  - deploymentconfig.yaml
+  - deployment-jira-mcp.yaml
+  - service-jira-mcp.yaml
 
 generatorOptions:
   disableNameSuffixHash: true
diff --git a/kustomize/base/secret-jira.yaml b/kustomize/base/secret-jira.yaml
@@ -0,0 +1,12 @@
+apiVersion: v1
+kind: Secret
+metadata:
+  name: bugzooka-jira
+  namespace: ${BUGZOOKA_NAMESPACE}
+  annotations:
+    kubernetes.io/service-account.name: default
+type: Opaque
+stringData:
+  JIRA_BASE_URL: "${JIRA_BASE_URL}"
+  JIRA_TOKEN: "${JIRA_TOKEN}"
+  JIRA_ALLOWED_PROJECTS: "${JIRA_ALLOWED_PROJECTS}"
diff --git a/kustomize/base/service-jira-mcp.yaml b/kustomize/base/service-jira-mcp.yaml
@@ -0,0 +1,17 @@
+apiVersion: v1
+kind: Service
+metadata:
+  labels:
+    app.kubernetes.io/instance: jira-mcp
+  name: jira-mcp
+  namespace: ${BUGZOOKA_NAMESPACE}
+spec:
+  ports:
+  - name: http
+    port: 3031
+    protocol: TCP
+    targetPort: 3031
+  selector:
+    app.kubernetes.io/instance: jira-mcp
+    app.kubernetes.io/name: jira-mcp
+  type: ClusterIP
diff --git a/mcp_config.json b/mcp_config.json
@@ -2,6 +2,8 @@
   "mcp_servers": {
     "orion_mcp_server": {
       "url": "http://localhost:3030/mcp",
+    "jira_mcp_server": {
+      "url": "http://localhost:3031/mcp",
       "transport": "streamable_http"
     }
   }
diff --git a/prompts.json b/prompts.json
@@ -1,7 +1,7 @@
 {
   "OPENSHIFT_PROMPT": {
     "system": "You are an expert in OpenShift, Kubernetes, and cloud infrastructure. Your task is to analyze logs and summaries related to OpenShift environments. Given a log summary, identify the root cause, potential fixes, and affected components. Be as consise as possible (under 5000 characters), but precise and avoid generic troubleshooting steps. Prioritize OpenShift-specific debugging techniques. Keep in mind that the cluster is ephemeral and is destroyed after the build is complete, but all relevant logs and metrics are available. Use markdown formatting for the output with only one level of bullet points, do not use bold text except for the headers.",
-    "user": "Here is the log summary from an OpenShift environment:\n\n{summary}\n\nBased on this summary, provide a structured breakdown of:\n- The OpenShift component likely affected (e.g., etcd, kube-apiserver, ingress, SDN, Machine API)\n- The probable root cause\n- Steps to verify the issue further\n- Suggested resolution, including OpenShift-specific commands or configurations.",
+    "user": "Here is the log summary from an OpenShift environment:\n\n{summary}\n\nBased on this summary, provide a structured breakdown of:\n- The OpenShift component likely affected (e.g., etcd, kube-apiserver, ingress, SDN, Machine API)\n- The probable root cause\n- Steps to verify the issue further\n- Suggested resolution, including OpenShift-specific commands or configurations",
     "assistant": "**Affected Component:** <Identified component>\n\n**Probable Root Cause:** <Describe why this issue might be occurring>\n\n**Verification Steps:**\n- <Step 1>\n- <Step 2>\n- <Step 3>\n\n**Suggested Resolution:**\n- <OpenShift CLI commands>\n- <Relevant OpenShift configurations>"
   },
   "ANSIBLE_PROMPT": {
diff --git a/requirements.txt b/requirements.txt
