The Featured Authorized Partner for RabbitMQ — named by the engineers who build it
AceMQ is the Featured Authorized Partner for RabbitMQ, named by the RabbitMQ Core Engineering Team — the people who write and maintain the broker. That recognition covers RabbitMQ support, licensing and professional services, and it makes AceMQ the only RabbitMQ partner with a direct line to the core team. When an escalation needs an answer that is not in the documentation, it does not stop at a support tier.
You do not have to take our word for it — RabbitMQ lists AceMQ on its own site.
See AceMQ listed on rabbitmq.comYou probably need this if…
Where you are now, and where you end up
Concrete state changes, not deliverable counts. This is what actually differs about your RabbitMQ estate when the engagement closes.
An assistant answers RabbitMQ questions from training data and whatever someone pasted into the chat.
The assistant reads live queue depth, consumer counts, rates, alarms and policies from your cluster before it answers.
Finding the queue behind a memory alarm means several tabs of the management UI and a few rabbitmqctl commands.
An engineer asks why the alarm fired and gets the backlogged queues, their consumers and the likely cause, with the data behind it.
The MCP setups on the table expect administrator credentials and can change the broker with no approval step.
Read-only by default, a least-privilege RabbitMQ user, and write actions that stay off until you allow them and approve each call.
Nobody can say which agent looked at the broker, what it asked for or what it changed.
Every tool call is in an audit log: which client, which tool, which arguments, when, and what came back.
An open-source integration works until it breaks, and then the question is who maintains it.
AceMQ licenses, maintains and supports the server, and the engineer who answers knows both the integration and RabbitMQ.
What's covered
How it actually runs
Every phase has a defined duration and a concrete artifact handed over at the end of it. You always know what stage you're in and what you've received.
Inquiry and Demo
Tell us which clusters you run, which AI tools your team uses and what you want them to do. We show the server working against a test broker, including the read-only tools, the approval step and the audit log.
- Live demo against a test broker
- Answers on fit for your clients and clusters
- Outline of licensing and support options
Scoping
We agree which clusters and virtual hosts the server can see, whether any write actions should be allowed and who approves them, where it runs, and where the audit log goes. Your security team gets the details it needs to review it.
- Cluster and virtual host scope
- Write-action allow-list, or confirmation of read-only
- RabbitMQ user and permission plan
- Quote for license and support
Deployment in Your Environment
Your team installs the server inside your network with an AceMQ engineer alongside. We create the least-privilege RabbitMQ user, configure TLS, connect your MCP clients and confirm the guardrails behave as agreed before anyone relies on it.
- Server running inside your network
- Least-privilege RabbitMQ user with the monitoring tag
- MCP clients connected and tested
- Audit log flowing to your chosen destination
Supported Operation
Updates, fixes and questions go through AceMQ support. If an assistant surfaces a broker problem your team wants help with, the same support relationship covers the cluster, so there is no handoff between an integration vendor and a RabbitMQ vendor.
- Updates and fixes to the server
- Support for the integration and its configuration
- Optional 24/7 RabbitMQ support or managed services for the cluster
What a RabbitMQ MCP server is
MCP, the Model Context Protocol, is an open standard for connecting AI applications to external systems. An AI application, the host, runs MCP clients that connect to MCP servers. Each server offers tools the model can call, resources it can read and prompts it can use. Servers run locally over standard input and output, or remotely over HTTP.
A RabbitMQ MCP server is one of those servers, with RabbitMQ on the other side. When an engineer asks an assistant why the orders queue is growing, the assistant calls the server's tools. The server queries the RabbitMQ management HTTP API, returns depth, consumers and rates, and the assistant answers from that data instead of from memory.
That puts the server in the path between an AI tool and a production broker, which is why AceMQ built it around what it will not do: it does not change anything unless you allow it, it holds no more RabbitMQ permissions than it needs, and it writes down every call it serves.
What it does, and what stays off unless you turn it on
- On by default: inspection — Listing and reading queues, exchanges, bindings, connections, channels, consumers, policies and definitions, plus node health, alarms, queue depth and message rates.
- On by default: diagnosis — Explaining a backlog or a memory alarm, and comparing configuration against RabbitMQ practice for queue types, dead-lettering, delivery limits and length limits.
- Off by default: write actions — Purging a queue, moving messages with a shovel and changing policies. Each one is enabled separately through an allow-list, can be limited to named virtual hosts or queues, and needs explicit approval on every call.
- Always on: the audit log — Every tool call, read or write, is recorded with its arguments, result and time.
Least privilege applies on the RabbitMQ side as well. The monitoring tag lets a user see node-level data, all virtual hosts and other users' connections without being able to manage users, virtual hosts or permissions. Queue permissions are a separate decision: in RabbitMQ, purging a queue needs only read permission on it, so we size the server's user to the actions you have actually allowed rather than relying on the tag alone.
The server runs inside your network. What it returns goes to the AI client you connect, and from there to that client's model provider under your agreement with them. Choose clients, and decide which clusters each one may see, with that in mind.
Which AI assistants and coding agents can use it
Any MCP-compatible client can connect. The ones engineering teams ask about most are Claude Desktop and Claude Code, Cursor, and VS Code with GitHub Copilot. All of them can run MCP servers locally. Cursor asks for approval before it runs an MCP tool by default, and VS Code can ask you to confirm each tool call, which adds a client-side check on top of the server's own approval step.
ChatGPT connects to remote MCP servers added as custom connectors, which means publishing an HTTPS endpoint that OpenAI's service can reach. That is a different network decision from a server that never leaves your environment, and we work through it with you during scoping if ChatGPT is on your list.
Real RabbitMQ Results
See how enterprises trust AceMQ for their most critical RabbitMQ workloads.
Questions about RabbitMQ agent access
Talk to a RabbitMQ Expert
Send us a message and we'll follow up within one business day — or book a free 30-min consultation directly.
305-204-2607info@acemq.comMiami, FL 33130
Prefer to talk now? Call us directly or use the consultation tab to find a time that works.