Statec Lu vs Markdownify MCP
A side-by-side look at the Statec Lu and Markdownify MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Statec Lu for data science tools work as a local process; choose Markdownify MCP for data science tools. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Statec Lu when
- You need dedicated capabilities in the Data Science Tools domain.
- You prefer a local stdio subprocess transport.
- You want tools like
list_dataflows, dataflow_structure, get_data.
Choose Markdownify MCP when
- You need dedicated capabilities in the Data Science Tools domain.
- Its auth model fits you: No auth required.
- You have the keys it needs:
MARKITDOWN_PATH, REPOMIX_PATH, MD_ALLOWED_PATHS, MD_SHARE_DIR. - You want tools like
youtube-to-markdown, pdf-to-markdown, bing-search-to-markdown.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Data Science Tools | Data Science Tools |
| Quality signal | 59/100 · Good | 56/100 · Good |
| Install command | Confirmed | Not confirmed yet |
| Transport | Local subprocess (stdio) | — |
| Auth | Not declared | No auth required |
| Pricing | Not declared | Free |
| Required env vars | None listed | MARKITDOWN_PATHREPOMIX_PATHMD_ALLOWED_PATHSMD_SHARE_DIR |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 2,997 |
| Directory activity | 1 views 0 installs 0 upvotes | 4 views 0 installs 0 upvotes |
| Tools | 3 | 10 |
| Full listing | View Statec Lu | View Markdownify MCP |
Tools & capabilities
Statec Lu tools 3
list_dataflowsBrowse or keyword-search STATEC (Luxembourg statistics) datasets, called "dataflows". Each result has an `id` (e.g. "DF_A1100", the dataflowRef you pass to get_data / dataflow_structure) and an English name plus a short description (publication date, periodicity, author, category). STATEC publishes hundreds of datasets, so pass `query` to filter unless you really want the whole catalog. Example: list_dataflows({ query: "population" }) or list_dataflows({ query: "unemployment" }).dataflow_structureGet the structure (Data Structure Definition) of one STATEC dataset: its ordered dimensions and, for each, the valid codes. Use this BEFORE get_data to learn how to build the dot-separated SDMX `key`. The key has one position per dimension, in `dimension_order`; an empty position is a wildcard. Example: dataflow_structure({ dataflow_id: "DF_A1100" }).get_dataPull observations from a STATEC dataset. `key` is a dot-separated SDMX dimension filter, one position per dimension in the order given by dataflow_structure; leave a position empty to wildcard it. Fetch dataflow_structure first to know the dimension order and valid codes. Example: get_data({ dataflow_id: "DF_A1100", key: "Valeur..A", start_period: "2010", end_period: "2020" }) picks VARIABLE=Valeur, wildcards SPECIFICATION, FREQ=A (annual). Omit `key` (or pass "") to fetch all series — caution, this can be large. Returns decoded series with their dimension labels and per-period values.
Markdownify MCP tools 10
youtube-to-markdownConvert YouTube videos to Markdownpdf-to-markdownConvert PDF files to Markdownbing-search-to-markdownConvert Bing search results to Markdownwebpage-to-markdownConvert web pages to Markdownimage-to-markdownConvert images to Markdown with metadataaudio-to-markdownConvert audio files to Markdown with transcriptiondocx-to-markdownConvert DOCX files to Markdownxlsx-to-markdownConvert XLSX files to Markdownpptx-to-markdownConvert PPTX files to Markdownget-markdown-fileRetrieve an existing Markdown file. File extension must end with: *.md, *.markdown.
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.
Statec Lu
{
"mcpServers": {
"statec-lu": {
"command": "npx",
"args": [
"-y",
"@pipeworx/mcp-statec-lu"
]
}
}
}
Markdownify MCP
No confirmed install command for Markdownify MCP yet — follow the setup steps linked from its listing page rather than a guessed package name.
Frequently asked questions
Statec Lu is categorized under Data Science Tools and uses a local stdio subprocess. Markdownify MCP belongs to Data Science Tools and uses an install path we have not confirmed yet. Pick Statec Lu for data science tools work and Markdownify MCP 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. Markdownify MCP has no confirmed install command yet — follow its own setup instructions.
Statec Lu has no declared pricing — check the project's own site. Markdownify MCP is listed as free. Auth: no auth required. 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 statec-lu and zcaceres-markdownify-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Statec Lu has a quality signal of 59/100 (Good) with 1 views, 0 installs and 0 GitHub stars. Markdownify MCP has 56/100 (Good) with 4 views, 0 installs and 2,997 GitHub stars.