広告掲載
MCP.so
ログイン

OpenStack MCP + Agent PoC

@Akrog

リポジトリ

基本情報

カテゴリ

AI とエージェント

トランスポート

stdio

作者

Akrog

OpenStack MCP + Agent PoC について

An OpenStack MCP server PoC

#openstack#mcp#agent#poc

OpenStack MCP + Agent PoC の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-openstack": {
      "command": "uv",
      "args": [
        "run",
        "main.py",
        "--config",
        "../servers.yaml"
      ]
    }
  }
}

OpenStack MCP + Agent PoC のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is OpenStack MCP + Agent PoC?

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 agent interacts with these servers via an LLM.

How to use OpenStack MCP + Agent PoC?

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.

Key features of OpenStack MCP + Agent PoC

  • 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.

Use cases of OpenStack MCP + Agent PoC

  • Quickly test OpenStack API interaction through an LLM.
  • Query OpenStack resources (e.g., flavors, servers) using natural language.
  • Experiment with MCP‑based tool use for OpenStack administration.

よくある質問

1

What prerequisites are needed to run it?

You need access to an OpenStack deployment, an LLM endpoint, and the `uv` package manager.

2

How do I configure the OpenStack client?

Place `clouds.yaml` and `secure.yaml` in the `agent/` directory or `~/.config/openstack/` as described in the OpenStack client documentation.

3

Where is the LLM token stored?

Create a file named `llm.token` in the `agent/` directory containing the secret/token for the OpenAI LLM endpoint.

4

Can I use any OpenStack deployment?

Yes, you only need to replace the placeholder URLs in `servers.yaml` with your cluster’s Nova, Cinder, and Glance public endpoints.

5

Does the agent have memory?

No, each prompt is a clean prompt for the LLM—there is no memory between turns.

コメント

「AI とエージェント」の他のコンテンツ

Orthogonal

orthogonal

Orthogonal MCP gives AI agents one connection to discover, call, and pay for external tools and data APIs. Instead of integrating separate providers for company intelligence, web research, scraping, enrichment, and finan

q-ring

I4cTime

Quantum-inspired keyring for AI coding agents. Secure secrets with superposition, entanglement, tunneling, and teleportation — CLI + 44 MCP tools.

3

strac-mcp-dlp

strac-io

Detect and redact PII, PHI, PCI and secrets — SSNs, credit cards, passports, API keys and cloud credentials — in text and in local files, using the Strac DLP API. Five tools: redact_text, detect_sensitive_data, detect_fi

3

localscreenshot - website screenshot mcp for ai agents

localscreenshot is a Website screenshot MCP server and API available at https://localscreenshot.com/api. Localscreenshot screenshot api turns any public web page into an image or a PDF. Take the capture from one of 227 c

Pocket Network Agentic Marketplace: Pay-per-Call APIs

Pocket Network Foundation

MCP server for the Pocket Network agentic marketplace: search our catalog of data services and utilities and call them, paying per request in USDC on Base with x402. No account or API key. Search and describe are free; p

広告掲載