# parliamentary-nlp-mcp

> parliamentary-nlp-mcp — alissonf216-parliamentary-nlp-mcp. Use this tool when you need to analyze Brazilian parliamentary speeches for hate speech and offensive language, as it audits texts and returns classification, confidence scores, and recommendations for human review. It solves problems related to monitoring and regulating harmful content in political discourse, providing valuable insights for policymakers and researchers. The tool takes in parliamentary speech texts and outputs classification results, confidence levels, and review recommendations through a BERTimbau-based interface.

Canonical page: https://skillsregistry.net/skills/alissonf216-parliamentary-nlp-mcp  
JSON: https://api.skillsregistry.net/v1/skills/alissonf216-parliamentary-nlp-mcp

## Description

MCP server that audits Brazilian parliamentary speeches for hate speech and offensive language using a fine-tuned BERTimbau classifier, returning classification, confidence, and human review recommendations.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/y4a79txf8n)
- **Repository:** <https://github.com/alissonf216/parliamentary-nlp-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": "alissonf216-parliamentary-nlp-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alissonf216-parliamentary-nlp-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alissonf216-parliamentary-nlp-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