# scorecard_mcp

> Use this tool when you need to analyze OpenSSF Scorecard security assessments for open source projects by asking natural language questions, solving problems related to project security and vulnerability evaluation. It takes natural language queries as input and provides relevant security assessment information as output. This tool is ideal for use cases where you want to quickly understand the security posture of open source projects.

Canonical page: https://skillsregistry.net/skills/steiza-scorecard-mcp  
JSON: https://api.skillsregistry.net/v1/skills/steiza-scorecard-mcp

## Description

Enables asking natural language questions about OpenSSF Scorecard security assessments for open source projects.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-01

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/dyudjtddnw)
- **Repository:** <https://github.com/steiza/scorecard-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": "steiza-scorecard-mcp"
    }
  }
}
```

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