# SpringOne 2025

> Use this tool when you need to access and analyze SpringOne 2025 conference session data, such as counting sessions by date or retrieving speaker information. It provides tools for session discovery, schedule planning, and speaker lookup, and accepts prompts for conference analysis, outputting relevant data and resources. Ideal for conference attendees seeking AI-powered insights and planning assistance.

Canonical page: https://skillsregistry.net/skills/danvega-springone  
JSON: https://api.skillsregistry.net/v1/skills/danvega-springone

## Description

This Spring Boot MCP server implementation by Dan Vega provides AI assistants with access to SpringOne 2025 conference session data through tools, prompts, and resources. Built with Spring AI's MCP server capabilities, it exposes session information via tools for counting sessions by date and retrieving all sessions, includes predefined prompts for conference analysis, and provides speaker biographical data as resources. The implementation demonstrates how to create MCP servers using Spring's programming model with JSON data loading, making it useful for conference attendees wanting AI-powered session discovery, schedule planning, and speaker information lookup.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/danvega-springone)
- **Repository:** <https://github.com/danvega/springone-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "danvega-springone"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/danvega-springone` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/danvega-springone/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt