OpenStack MCP + Agent PoC
About
A proof-of-concept that runs an OpenStack Model Context Protocol (MCP) server alongside a basic agent companion program to test it. It uses the OpenStack code generator to create OpenAPI specs, then serves them with mcp-openapi as one MCP server per OpenStack component. The…
Details
- Author
- Akrog
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- Generates OpenAPI specs from OpenStack using openstack-code-generator.
- Serves specs as per‑component MCP servers via mcp-openapi.
- Includes a minimal agent to query OpenStack resources through an LLM.
- Filters REST API paths to limit tool count and context window.
- Requires uv package manager, an OpenStack deployment, and an LLM.
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
OpenStack MCP + Agent PoCCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Clone the repository with submodules, edit servers.yaml to replace placeholder URLs for Nova, Cinder, and Glance, then run the server from the mcp-openapi directory with uv run main.py --config ../servers.yaml. In a second terminal, configure OpenStack client config (e.g., clouds.yaml) and LLM credentials in agent/agent.json, then run the agent with uv run main.py.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"openstack mcp + agent poc": {
"mcp-openstack": {
"command": "uv",
"args": [
"run",
"main.py",
"--config",
"../servers.yaml"
]
}
}
}
}McpServers
{
"mcp-openstack": {
"command": "uv",
"args": [
"run",
"main.py",
"--config",
"../servers.yaml"
]
}
}OpenStack MCP + Agent PoC
This repository contains the code and instructions to run an OpenStack MCP
server and a very basic agent companion program to test it.
The approach taken in this PoC is:
- Use the OpenStack codegenerator project (openstack-code-generator) to
create OpenAPI Specs for OpenStack.
- Use the mcp-openapi project to start multiple MCP servers (one per
OpenStack component) from a filtered version of their full OpenAPI
specifications.
- Use the agent code to interact with the MCP servers via an LLM.
You don't need all this for a quick test, you can just follow the
QuickStart guide, but if you want to do something different
you'll need to go through the Running things guide.
QuickStart
We assume you have access to an OpenStack deployment and to an LLM, as they are
required to run things.
You'll also need the uv package manager. If you don't you can install it with
sudo dnf install uv.
We'll be using 2 terminals, one for the MCP server and another for the Agent.
Clone this repository
We'll clone this repository with just the minimum external projects necessary
to run things.
$ git clone --shallow-submodules \
--recurse-submodules=mcp-openapi \
https://github.com/Akrog/mcp-openstack.git
$ cd mcp-openstack
Run the MCP server
First we need to configure the MCP server, and for that we'll edit the
servers.yaml file and replace the <NOVA_PUBLIC_URL>, <CINDER_PUBLIC_URL>,
and <GLANCE_PUBLIC_URL> placeholders with the values of our cluster.
You'll notice that only a subset of REST API paths are being enabled to avoid
having tool many tools that could go over our model's context window or induce
hallucinations.
Now we can run the server:
$ cd mcp-openapi
$ uv run main.py --config ../servers.yaml
We leave this service running on this terminal and go to another terminal.
Run the Agent
In another terminal we'll go into the agent directory:
$ cd agent
OpenStack client config
Now we'll make sure the configuration for the OpenStack client is available in
one of the standard locations as described in the
documentation:
- agent/
- ~/.config/openstack/
If we are running an OSP 18 cloud we can get this with:
$ oc cp openstackclient:/home/cloud-admin/.config/openstack/clouds.yaml ./clouds.yaml
$ oc cp openstackclient:/home/cloud-admin/.config/openstack/secure.yaml ./secure.yaml
LLM config
We'll create an llm.token file with the secret/token for the OpenAI LLM
endpoint we want to use.
Then edit the agent.json file to replace the <LLM_URL> placeholder with our
LLM's address and replace <MODEL> with the model we want to use. For example
for Anthropic we could have something like this:
{
"base_url": "https://api.anthropic.com/v1",
"model": "claude-3-5-haiku-20241022",
< ... >
}
Run the agent
Now we just need to start the agent:
$ uv run main.py
Enjoy
We can now ask things about our deployment and see the REST API calls on the
MCP server terminal.
For example to get the nova flavors we could do:
$ uv run main.py
LLM: claude-3-5-haiku-20241022 @ https://api.anthropic.com/v1 Tools: 46
>>> What are my flavors?
Be aware that the agent doesn't have memory, so each prompt will be a clean
prompt for the LLM.
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