# MCP-studies

> MCP-studies — viniciusfinger-mcp-studies. Use this tool when you need to standardize context provision for large language models (LLMs) and integrate applications with open protocols. It solves problems related to inconsistent context sharing and enables seamless interaction between apps and LLMs. With git capabilities, MCP-studies accepts application context as input and outputs standardized protocol implementations for efficient LLM integration.

Canonical page: https://skillsregistry.net/skills/viniciusfinger-mcp-studies  
JSON: https://api.skillsregistry.net/v1/skills/viniciusfinger-mcp-studies

## Description

MCP is an open protocol that standardizes how applications provide context to large language models (LLMs)

## Trust

- **Trust score (0–1):** 0.96
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/viniciusfinger/MCP-studies)

## 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": "viniciusfinger-mcp-studies"
    }
  }
}
```

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