git clone https://github.com/ibm-ai-platform/ibm-concert-mcp.git
cd ibm-concert-mcp

# Workflow monitor
pip install -r requirements.txt

# Knowledge server (separate — heavier ML dependencies)
pip install -r requirements-knowledge.txt

uv venv && source .venv/bin/activate
uv pip install -r requirements.txt

cp .env.example .env

{
  "mcpServers": {
    "concert-workflow-monitor": {
      "command": "uvx",
      "args": [
        "concert-workflow-monitor"
      ],
      "env": {
        "CONCERT_API_KEY": "<your-concert-api-key>",
        "SLACK_WEBHOOK_URL": "<your-slack-webhook-url>",
        "MCP_TRANSPORT": "stdio"
      }
    },
    "concert-knowledge": {
      "command": "uvx",
      "args": [
        "--from",
        "ibm-concert-mcp[knowledge]",
        "python",
        "-m",
        "ibm_concert_mcp.knowledge.server"
      ],
      "env": {
        "SUPABASE_URL": "<your-supabase-url>",
        "SUPABASE_PUBLISHABLE_KEY": "<your-supabase-key>",
        "MCP_TRANSPORT": "stdio"
      }
    }
  }
}

export CONCERT_API_KEY=<your-key>
export SLACK_WEBHOOK_URL=<your-webhook>
export MCP_TRANSPORT=sse
export MCP_HOST=0.0.0.0
export MCP_PORT=8000
python -m ibm_concert_mcp.server

{
  "mcpServers": {
    "concert-workflow-monitor": {
      "type": "sse",
      "url": "http://<your-server>:8000/sse"
    }
  }
}

"Check if any Concert workflows are failing"
→ get_failing_workflows()

"Diagnose the akshay-test-fail workflow"
→ get_workflow_diagnosis("akshay-test-fail")

"Try to fix it automatically"
→ remediate_workflow("akshay-test-fail", strategy="auto")

"Post the result to Slack"
→ send_slack_alert(...)

"Show me the top Priority 1 CVEs"
→ get_concert_cve_summary(priority="1")

"Trigger package remediation for my-app, assign to jsmith"
→ trigger_package_remediation(application_name="my-app", git_repo="...", github_assignee="jsmith")

"Upload the updated SBOM"
→ upload_scan_to_concert(scan_type="package_sbom", ...)

"The recommendation didn't help — what actually fixed it was restarting the gateway pod"
→ record_recommendation_feedback("akshay-test-fail", vote="down", actual_fix="restart gateway pod")

"What has the agent learned so far?"
→ get_recommendation_learnings()

WORKFLOWS = [
    # (adapter_name, environment, workflow_name, display_name)
    ("my-adapter", "prod", "my-workflow", "My Workflow Display Name"),
]

AI Agent (Bob / Claude / etc.)
        │
        │  MCP (stdio or SSE)
        ▼
concert-workflow-monitor ──► IBM Concert Workflows API
        │                ──► OpenShift (oc rollout restart)
        │                ──► Slack (Incoming Webhook)
        │                ──► Supabase (incident DB)
        │
concert-knowledge ──────────► Supabase pgvector (Concert docs RAG)