# paraview-mcp

> paraview-mcp — failed33-paraview-mcp. Use this tool when you need to integrate large language models with ParaView for enhanced data visualization and analysis. It solves problems of complex data processing and automation by enabling direct Python code execution and pipeline control within the ParaView GUI. The tool accepts Model Context Protocol inputs and outputs controlled pipeline results, ideal for use cases requiring seamless interaction between LLM assistants and ParaView.

Canonical page: https://skillsregistry.net/skills/failed33-paraview-mcp  
JSON: https://api.skillsregistry.net/v1/skills/failed33-paraview-mcp

## Description

Connects ParaView to LLM assistants via the Model Context Protocol, enabling direct Python code execution and pipeline control within the ParaView GUI.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** devops-ci
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/erzem15o2d)
- **Repository:** <https://github.com/failed33/paraview-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": "failed33-paraview-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/failed33-paraview-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/failed33-paraview-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