# PyKernel MCP

> Use this tool when you need to execute Python code with persistent state and inline visualizations, leveraging libraries like numpy, pandas, and matplotlib. It solves problems requiring stateful computation, data analysis, and visualization, providing a seamless interface for inputting code and outputting results and visualizations. Ideal for data science, scientific computing, and education use cases.

Canonical page: https://skillsregistry.net/skills/dosinga-pykernel-mcp  
JSON: https://api.skillsregistry.net/v1/skills/dosinga-pykernel-mcp

## Description

MCP server that provides a persistent IPython kernel for executing Python code with pre-loaded numpy, pandas, and matplotlib, supporting stateful computation and inline visualizations.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/jy3epqdzxy)
- **Repository:** <https://github.com/DOsinga/pykernel_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": "dosinga-pykernel-mcp"
    }
  }
}
```

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