Jupyter MCP Server vs Math
A side-by-side look at the Jupyter MCP Server and Math MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Jupyter MCP Server for data science tools work as a local process; choose Math for data science tools. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Jupyter MCP Server when
- You need dedicated capabilities in the Data Science Tools domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
Choose Math when
- You need dedicated capabilities in the Data Science Tools domain.
- You want tools like
calculate, convert_units, statistics.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Data Science Tools | Data Science Tools |
| Quality signal | 48/100 · Fair | 37/100 · Fair |
| Install command | Confirmed | Not confirmed yet |
| Transport | Local subprocess (stdio) | — |
| Auth | No auth required | Not declared |
| Pricing | Free | Not declared |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 1,312 | 0 |
| Directory activity | 3 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | Not listed | 5 |
| Full listing | View Jupyter MCP Server | View Math |
Tools & capabilities
Jupyter MCP Server tools
No tool names declared yet. Check the project README from the listing page.
Math tools 5
calculateEvaluate math expressions safely (no `eval`). Supports arithmetic operators (`+`, `-`, `*`, `/`, `^`, `%`), parentheses, functions (`sqrt`, `abs`, `floor`, `ceil`, `round`, `log`, `ln`, `sin`, `cos`, `tan`, `min`, `max`, `pow`), constants (`pi`, `e`), and named variables.convert_unitsConvert between units across six categories:statisticsStatistical analysis on datasets: mean, median, mode, variance, standard deviation, min, max, range, percentile, correlation between two arrays, and a full summary mode.format_numberFormat numbers as: currency (`$1,234.56`), percentage, scientific notation, binary, octal, hexadecimal, significant figures, or with thousands separators.percentage_calcCommon percentage operations: X% of Y, what percent X is of Y, percentage change between two values, tip calculator, discount calculator, and markup calculator.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Jupyter MCP Server
{
"mcpServers": {
"datalayer-jupyter-mcp-server": {
"command": "uvx",
"args": [
"jupyter-mcp-server@latest"
]
}
}
}
Math
No confirmed install command for Math yet — follow the setup steps linked from its listing page rather than a guessed package name.
Frequently asked questions
Jupyter MCP Server is categorized under Data Science Tools and uses a local stdio subprocess. Math belongs to Data Science Tools and uses an install path we have not confirmed yet. Pick Jupyter MCP Server for data science tools work and Math for data science tools.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client. Math has no confirmed install command yet — follow its own setup instructions.
Jupyter MCP Server is listed as free. Auth: no auth required. Math has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add datalayer-jupyter-mcp-server and math as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Jupyter MCP Server has a quality signal of 48/100 (Fair) with 3 views, 0 installs and 1,312 GitHub stars. Math has 37/100 (Fair) with 1 views, 0 installs and 0 GitHub stars.