Jupyter MCP Server vs Statbel Be
A side-by-side look at the Jupyter MCP Server and Statbel Be 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 Statbel Be for data science tools as a local process. 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 Statbel Be when
- You need dedicated capabilities in the Data Science Tools domain.
- You prefer a local stdio subprocess transport.
- You want tools like
list_views, get_view, list_datasets.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Data Science Tools | Data Science Tools |
| Quality signal | 48/100 · Fair | 57/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | 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 | 1,308 | 0 |
| Directory activity | 3 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | Not listed | 4 |
| Full listing | View Jupyter MCP Server | View Statbel Be |
Tools & capabilities
Jupyter MCP Server tools
No tool names declared yet. Check the project README from the listing page.
Statbel Be tools 4
list_viewsBrowse/search Statbel (Statistics Belgium, be.STAT) saved statistical views. Each view is a pre-built table over a dataset and carries a single locale (nl/fr/de/en). Returns id, name, locale, dataSourceId and publish dates. Filter by case-insensitive substring of the view name (matches in any language).get_viewMetadata for one Statbel view by its id (a UUID, e.g. from list_views). Returns the view object: name, locale, dataSourceId (the underlying dataset), and publish/change dates. To get the dataset description in all available languages, pass the returned dataSourceId to get_dataset.list_datasetsBrowse/search Statbel datasets (be.STAT "datasources"). Each dataset has a `name` code (e.g. "IM_EAF_HOUSE_SALES_IDX"), a `descriptions` map with one entry per supported language (nl/fr/de/en), a category id, supportedLocales, and last-update timestamps. Filter by case-insensitive substring matched against the dataset code and all-language descriptions.get_datasetMultilingual metadata for one Statbel dataset by its id (a UUID, e.g. the dataSourceId from a view). Returns the dataset code `name`, the `descriptions` map (nl/fr/de/en text), supportedLocales, defaultLocale, category id and update dates.
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"
]
}
}
}
Statbel Be
{
"mcpServers": {
"statbel-be": {
"command": "npx",
"args": [
"-y",
"@pipeworx/mcp-statbel-be"
]
}
}
}
Frequently asked questions
Jupyter MCP Server is categorized under Data Science Tools and uses a local stdio subprocess. Statbel Be belongs to Data Science Tools and uses a local stdio subprocess. Pick Jupyter MCP Server for data science tools work and Statbel Be 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.
Jupyter MCP Server is listed as free. Auth: no auth required. Statbel Be 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 statbel-be 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 1,308 GitHub stars. Statbel Be has 57/100 (Good) with 1 views, 0 installs and 0 GitHub stars.