# VersionOne MCP Server

> Use this tool when you need to integrate VersionOne data into AI workflows, enabling queries on stories, features, and their details. It solves problems related to accessing and structuring VersionOne data for AI-assisted tasks, providing a standardized output for further processing. This tool accepts query inputs and returns structured data outputs, ideal for use cases requiring VersionOne data integration and analysis.

Canonical page: https://skillsregistry.net/skills/quantiser-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/quantiser-mcp-server

## Description

Enables AI assistants to query VersionOne for stories, features (epics), and their details with structured output.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/y0p6nx60nh)
- **Repository:** <https://github.com/Quantiser/mcp-server>

## 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": "quantiser-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/quantiser-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/quantiser-mcp-server/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