WildFly
This WildFly MCP server, developed by the WildFly team, provides a Java-based interface for AI assistants to interact with and manage WildFly application servers. Built using Quarkus and leveraging the Model Context Protocol, it offers tools for monitoring server status, resource consumption, log analysis, and configuration management. The implementation focuses on simplifying WildFly server administration through natural language interactions, making it easier for AI models to assist in troubleshooting, performance monitoring, and server management tasks. It's particularly useful for DevOps teams and system administrators who want to integrate AI assistance into their WildFly server management workflows, enabling efficient server diagnostics and configuration without requiring deep knowledge of WildFly's management interfaces.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- devops-ci
- Source
- PulseMCP
- Repository
- github.com/wildfly-extras/wildfly-mcp
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve WildFly from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.