MQ-Sentinel

Production-grade, read-only IBM MQ diagnostic MCP server that AI agents can safely use — with zero hallucinations.

I built this as a serious side project to solve a real, high-stakes problem in enterprise environments. It is now a strong public portfolio piece demonstrating systems engineering, security, observability, production deployment, and building safe infrastructure for AI agents.

0.3.0 — 8 diagnostic tools across all 10 IBM MQ flavors. Read-only by design. Prompt-injection firewall. OIDC + RBAC. Hash-chained audit. Verified IBM Knowledge Center citations (CI-enforced). Production Helm with HPA + air-gapped packaging.

GitHub: https://github.com/pramodreddyboddu/mq-sentinel
Live Demo: https://mq-sentinel.io
Get it in front of people: docs/LAUNCH.md

The Problem I Solved

Enterprise IBM MQ teams waste hours diagnosing issues like:

• 2035 NOT_AUTHORIZED storms
• Exploding DLQs
• Native HA replica lag and split-brain
• Stale cluster members
• z/OS mysteries

Traditional tools require deep expertise and manual log diving. Handing an LLM raw MQ access is unacceptable for security and compliance teams.

MQ-Sentinel gives Claude, Cursor, Grok, and other agents a safe MCP interface that returns accurate, cited diagnostics without ever hallucinating or executing destructive commands.

The Problem

IBM MQ teams (banks, telcos, insurance, gov) waste hours on:

• 2035 NOT_AUTHORIZED channel storms
• Exploding DLQs
• Native HA replica lag / split-brain
• Stale cluster members
• z/OS QSG mysteries

Traditional tools require deep MQSC knowledge and grepping logs. Giving an LLM direct MQ access is a non-starter for security/compliance teams.

MQ-Sentinel solves this by giving Claude, Cursor, Grok, etc. a safe, read-only MCP interface that returns typed Root Cause + Fix Steps + verified IBM docs — never fabricates, never executes destructive commands.

🎬 See it in 90 seconds

git clone https://github.com/pramodreddyboddu/mq-sentinel.git
cd mq-sentinel
make demo

Watch MQ-Sentinel diagnose a real 2035 NOT_AUTHORIZED, an INDOUBT channel, a 1247-message DLQ, and a Native HA replica disconnect — all against the bundled fixture sandbox. No live IBM MQ required.

Want to record it for sharing? make demo-record produces a browser-playable asciinema cast.

Quick self-check (no MQ needed):

uv run mq-sentinel doctor
uv run mq-sentinel tools     # list all diagnostics
uv run mq-sentinel info      # overview + security highlights

Use it from Claude, Grok, Cursor, Gemini, ChatGPT

One MCP server — not a per-vendor plugin. Copy-paste configs: docs/mcp-clients.md.

List it where agents discover servers: official MCP Registry (server.json) + Smithery (smithery.yaml). ChatGPT needs a hosted HTTPS endpoint, not local stdio.

Architecture at a Glance

flowchart TB
    subgraph Client["MCP Client (Claude / Cursor / Grok)"]
        P[Prompt]
    end

    subgraph Sentinel["MQ-Sentinel (read-only)"]
        OIDC[OIDC + RBAC]
        RL[Rate Limiter]
        DISP[Tool Dispatcher]
        ALLOW[MQSC Allowlist]
        CONN[Connector<br/>(pymqi / fixture)]
        RCS[RCS Engine +<br/>KC Registry]
        SAN[Output Sanitizer]
        AUDIT[Hash-chained<br/>Audit Log]
    end

    subgraph MQ["IBM MQ (read-only service account)"]
        QM[Queue Managers]
    end

    P -->|MCP stdio / HTTP| OIDC
    OIDC --> RL --> DISP
    DISP --> ALLOW
    ALLOW --> CONN
    CONN -->|raw output| RCS
    RCS --> SAN
    SAN --> AUDIT
    CONN --> QM
    QM -.->|DISPLAY only| CONN

Safe by design. No LLM inside the server. Every citation verified in CI.

Why This Stands Out as a Portfolio Project

This is not a toy or weekend demo. It demonstrates real engineering depth:

• Systems + Security Engineering: Full threat model, multi-layer read-only enforcement, prompt-injection firewall, OIDC+RBAC, tamper-evident audit, hardened containers, SBOM + signed images.
• Production Operations: Production Helm (HPA, ServiceMonitor, NetworkPolicy), air-gapped packaging (RPM/DEB), observability out of the box.
• AI Agent Infrastructure: A complete, safe MCP server (stdio + HTTP) designed for real use by agents like Claude, Cursor, and Grok.
• Enterprise Domain Expertise: Deep coverage of IBM MQ across 10 topologies with version-aware, verified citations.
• Systematic Delivery: Executed a full 7-phase org-readiness plan with compliance artifacts that actual organizations need.

Built with Grok Build (primary coding partner) while maintaining strict engineering standards.

Full journey and plan: docs/ORG-READINESS-PLAN.md

See also: VISION.md · CONTRIBUTING.md · DEVELOPMENT.md

The Journey (Portfolio Story)

I built MQ-Sentinel to solve a painful, recurring problem in enterprise IBM MQ environments — and I treated the entire effort as a serious engineering and portfolio project.

I used Grok Build (xAI) as my primary coding partner from architecture through implementation, docs, Helm, compliance artifacts, and polish. Every major decision was deliberate: read-only first, citations that can't go stale, defense-in-depth, production packaging.

Key milestones:

• Designed threat model + multi-layer security architecture before writing the first tool
• Delivered 8 diagnostic tools across 10 MQ flavors with CI-enforced IBM Knowledge Center citations
• Production deployment (Helm + HPA + ServiceMonitor, distroless, air-gapped RPM/DEB)
• Full 7-phase org-readiness plan executed (see links above)
• 271+ tests (including security-negative tests), strict mypy, comprehensive docs for platform teams

This shows end-to-end ownership: deep domain knowledge, security by design, production operations, and shipping artifacts that real organizations can actually use.

This is my public portfolio project. It demonstrates systems engineering, security, observability, AI infrastructure, and disciplined delivery.

Built with Grok Build while holding high standards throughout.

Security posture — baked in, not bolted on

• Read-only always. Static MQSC allowlist (DISPLAY / DIS / PING CHANNEL only). Destructive verbs are rejected by three layers: tool, connector, MQ-side setmqaut.
• Prompt-injection firewall. Every MQ-sourced string is sanitized (control chars, zero-width, ANSI, unicode tag chars, jailbreak markers) and wrapped in a quarantine envelope before leaving the server.
• URL allowlist + live verification. Responses may only cite www.ibm.com; all other URLs are redacted. Every citation in the registry (20+ reason codes, 8 AMQ codes, 18 topic pages) is fetched daily in CI — a dead link fails the build, not the customer.
• Tamper-evident audit log. Hash-chained JSONL; mq-sentinel verify-audit detects any retroactive edit.
• OIDC + RBAC. Principals scoped to nonprod-read / prod-read / admin-audit. Cannot query prod QMs from a nonprod token.
• Hardened runtime. Distroless image, non-root, read-only FS, dropped capabilities, seccomp, network egress allowlist.
• Supply chain. SBOM, cosign-signed images, pip-audit + Trivy in CI, every PR security-gated.

See SECURITY.md and docs/threat-model.md.

Org / Enterprise Ready?
This project was deliberately built for real organizations (banks, gov, large enterprises). See the complete journey:

See VISION.md for the owner product principles and long-term thinking.

• Org-Readiness Plan — 7-phase plan executed end-to-end
• Production Guide + Platform Team Onboarding
• Security Posture + SOC2 Evidence Checklist
• RBAC & Auth Examples (Okta, Entra ID, Keycloak)
• Production Helm with HPA, ServiceMonitor, network policies, and fleet support
• Observability — Grafana + Prometheus alerts ready to import

Skills & Engineering Rigor (Portfolio Highlights)

What this project demonstrates:

• Systems & Security Engineering — Full threat model, prompt-injection defense, multi-layer read-only enforcement, OIDC+RBAC, hash-chained audit, distroless hardening.
• Observability & Production Operations — Metrics, dashboards, alerts, runbooks, air-gapped packaging, Helm productionization.
• AI Agent Infrastructure — Built a real, safe MCP server (stdio + HTTP) that LLMs can use without risk.
• Enterprise Systems — Deep IBM MQ knowledge across 10 topologies + version-aware diagnostics.
• Software Craftsmanship — 271+ tests (including security), strict mypy, ruff, CI-driven doc verification, SBOM + cosign signing.
• End-to-End Delivery — From idea to org-ready artifacts, including comprehensive documentation that platform teams can actually use.