WildFly MCP
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Enable generative AI capabilities for monitoring and managing WildFly servers through integrated tooling.
WildFly MCP Overview
What is WildFly MCP about?
WildFly MCP provides a set of tools that connect WildFly servers with generative‑AI chat interfaces, allowing administrators to interact with server monitoring and management functions using natural language.
How to use WildFly MCP?
- Deploy the WildFly MCP Server (found in
wildfly-mcp-server/) alongside your WildFly instance. - Optionally run the WildFly Chat Bot (
wildfly-chat-bot/) to expose a conversational interface that communicates with the MCP server. - Use the provided container images (
container-images/) for quick Kubernetes/OpenShift deployment, which bundle both the server and chat bot. - If your environment only supports STDIO, insert the MCP STDIO‑to‑SSE gateway (
mcp-stdio-sse-gateway/) to translate protocols. - For workflow testing, the Wait MCP Server (
wait-mcp-server/) can simulate delays.
Key features of WildFly MCP
- Seamless integration of generative AI chat with WildFly server operations.
- Ready‑to‑use container images for cloud‑native deployments.
- Protocol gateway converting STDIO to SSE for broader compatibility.
- Lightweight “wait” server to orchestrate timed actions in AI‑driven workflows.
- Extensible architecture based on the Model Context Protocol (MCP).
Use cases of WildFly MCP
- Natural‑language monitoring: Ask an LLM for current server health, logs, or metrics.
- AI‑guided troubleshooting: Describe an issue in plain text and receive suggested configuration changes.
- Automated administration: Issue deployment or reload commands via chat without manual CLI usage.
- Demo environments: Use the Wait MCP Server to illustrate step‑by‑step AI workflows.
- Cross‑tool integration: Connect existing chat applications to WildFly through the STDIO‑to‑SSE gateway.
FAQ from the WildFly MCP
Q: Do I need a specific LLM provider? A: The MCP server is agnostic; you can connect any LLM that can communicate over the defined protocol.
Q: Is there a Kubernetes operator? A: Not currently, but the provided container images can be deployed with standard manifests or Helm charts.
Q: How do I secure the communication? A: Use TLS in the underlying MCP transport and configure authentication tokens in the chat bot.
Q: Can I extend the server with custom commands? A: Yes, the MCP server is Java‑based; you can add new handlers to expose additional WildFly management actions.
Q: What is the purpose of the Wait MCP Server? A: It introduces a programmable delay, useful for pacing multi‑step AI interactions or simulating long‑running tasks.
WildFly MCP's README
WildFly MCP
This project aims to define tooling allowing WildFly users to benefenit from the Generative AI capabilities when monitoring and managing WildFly servers.
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WildFly MCP Server: A WildFly MCP server to integrate with your AI chatbot in order to interact with WildFly server using natural language.
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WildFly Chat Bot: A WildFly Chat Bot to interact with WildFly servers. This AI chatbot allows to also integrate MCP servers (STDIO and SSE protocol).
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Container Images: Container images for mcp server and the chat bot (that contains both the chat bot and the mcp server. Ready to interact with your WildFly servers on the cloud). Example of OpenShift deployment is provided.
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MCP STDIO to SEE protocol gateway: A Java gateway allowing to integrate SSE MCP servers in chat applications that only support STDIO protocol.
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Wait MCP Server: A simple MCP server that allows LLM to wait for some seconds. Can be useful in some workflow.
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WildFly MCP's Information
- Author
- wildfly-extras
- Category
- Development Tools
- Language
- Java
- License
- Apache License 2.0
- Stars
- 7
- Updated
- 21 days ago
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