# mcp-tool-card-spec

> mcp-tool-card-spec — mizcausevic-dev-mcp-tool-card-spec. Use this tool when you need to create per-tool disclosure documents for Model Context Protocol servers, providing detailed information on input/output schema, side effects, and performance metrics. It helps solve problems related to transparency and consistency in tool integration, allowing for informed decision-making and efficient auditing. This tool takes in tool specifications and outputs comprehensive documentation, making it ideal for use cases where standardized disclosure is required.

Canonical page: https://skillsregistry.net/skills/mizcausevic-dev-mcp-tool-card-spec  
JSON: https://api.skillsregistry.net/v1/skills/mizcausevic-dev-mcp-tool-card-spec

## Description

MCP Tool Cards v0.1 draft. Per-tool disclosure documents for Model Context Protocol servers: input/output schema, side-effect classification, tested-LLM matrix, latency, cost, audit surface. Layers on MCP without modifying it. Part of the Kinetic Gain Protocol Suite.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/mizcausevic-dev/mcp-tool-card-spec)

## 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": "mizcausevic-dev-mcp-tool-card-spec"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mizcausevic-dev-mcp-tool-card-spec` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mizcausevic-dev-mcp-tool-card-spec/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