Netcafe Tables is answering right now. Last checked 10 min ago. It exposes 15 tools. Last commit 16 Aug 2026.
Messy spreadsheets in, clean checkable tables out. Every result carries its arithmetic proof.
Uptime history
17 days of history · worst day 95%
17 days agonow
100.0%
Uptime 24h
91 of 91 checks
15
Tools
read from the server
687 ms
Response time
average over 24h
1
Stars
last commit 16 Aug 2026
Nothing serious here today
Today is the operative word: we check Netcafe Tables every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.
Connect this server
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 10 min ago.
run in your terminal
claude mcp add netcafe-tables --transport http https://ainetcafe.com/mcp/table?s=registry~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"netcafe-tables": {
"url": "https://ainetcafe.com/mcp/table?s=registry"
}
}
}~/.codex/config.toml
[mcp_servers.netcafe-tables]
url = "https://ainetcafe.com/mcp/table?s=registry".cursor/mcp.json
{
"mcpServers": {
"netcafe-tables": {
"url": "https://ainetcafe.com/mcp/table?s=registry"
}
}
}.vscode/mcp.json
{
"mcpServers": {
"netcafe-tables": {
"url": "https://ainetcafe.com/mcp/table?s=registry"
}
}
}Available tools 15
Read directly from the server with tools/list, grouped by what they act on.
If a tool disappears, we record the date.
csv
csv_to_chart
CSV (first column = labels, second = values) → chart PNG in one call.
csv_to_json
CSV (text or URL) → JSON array of objects (first row = keys). Returns a .json file.
csv_to_md_table
CSV (text or URL) → GitHub-flavoured Markdown table.
csv_to_qbo
Convert a transaction CSV into a .qbo / OFX bank-feed file that QuickBooks and similar accounting software import directly. Needs date, description and amount columns (or debit + credit). Pairs with extract_statement: statement PDF in, importable bank feed out.
xlsx
read_xlsx
Read an Excel .xlsx workbook (by URL) into rows — every sheet, or one you name. Returns cell values (not formula text), dates as YYYY-MM-DD instead of Excel serial numbers, and keeps leading zeros so ID/postcode columns are not silently mangled. Says plainly which sheet it used, which sheets are hidden, and where merged cells left blanks, instead of guessing for you.
write_xlsx
Build an Excel .xlsx file from rows (CSV text or JSON arrays), optionally several sheets at once. Numbers are written as real numbers so they sum in Excel, while values with leading zeros stay text so IDs and postcodes survive the round trip.
clean
clean_table
Tidies a spreadsheet export: removes duplicate rows, trims whitespace (half-width and full-width — Chinese exports are full of ), unifies the half-dozen ways a cell can say "empty" (NA / null / - / 无), drops empty rows and columns, and can split one column into several. Returns the cleaned CSV plus exactly what changed: rows in, rows out, duplicates removed, cells trimmed per column. It can also transpose rows/columns and unpivot a wide table into a long one. The row arithmetic is verified in code — if in − removed ≠ out, the response says so instead of handing back a table nobody can check. Use when a CSV came out of Excel or an export and needs cleaning before analysis.
dedupe
dedupe_entities
Find records in a supplier/customer/store list that are probably the SAME entity under different names — "北京星辰科技有限公司" vs "星辰科技(北京)" — by cross-checking name similarity against hard identifiers: tax ID (统一社会信用代码, checksum-verified), phone, domain, bank account, address. It never merges anything: it returns candidate groups with the evidence for each link, pairs that need human review, and — just as
diff
diff_tables
Matches rows across two CSVs on a key column and reports three things: keys only in A, keys only in B, and keys in both whose other columns disagree — naming the exact column and both values. Unlike reconcile_ledger this needs no amount column, so it also fits name lists, inventory counts, permission tables, and any "these two exports should match" check.
fix
fix_csv_encoding
Detect the real encoding of a CSV (GB18030, Shift-JIS, Windows-1252…), repair mojibake (UTF-8 that was read as Latin-1, e.g. "é"), and re-emit UTF-8 with a BOM so Excel opens it correctly.
json
json_to_csv
JSON array of objects → CSV file. Flattens keys, quotes fields containing commas.
match
match_transactions
Match bank statement lines to ledger/invoice entries when there is NO shared key — by amount, date window, reference numbers found inside free-text descriptions, and fuzzy counterparty names ("北京XX科技" vs "XX科技(北京)"). Handles split payments (one invoice paid in instalments, 1:N) and combined payments (one transfer covering several invoices, N:1). Its rule is: never guess — a pair is only auto-match
merge
merge_tables
Combines up to 20 CSVs into a single table. Headers do not have to match: columns are unioned and a file missing a column contributes blanks for it, so rows never shift silently — the failure mode that makes hand-merged spreadsheets untrustworthy. Reports each source file row count and checks in code that they sum to the merged total. Use for monthly exports, per-store sheets, or any set of files with the same subject but drifting headers.
reconcile
reconcile_ledger
Reconciles two sets of records — your books against a bank, platform, or supplier statement. Matches rows on a key column, compares an amount column, and returns three lists: only in A, only in B, and same key but different amount. Amounts are compared in integer cents, so 0.1 + 0.2 never invents a phantom difference for someone to chase. The response also proves the result: the listed differences are re-added and must equal the gap between the two totals, checked in code. Use for month-end close, platform payouts vs orders, or any "these two numbers should agree and do not" problem. This is the job people do by hand with VLOOKUP or a groupby and then cannot prove they got right.
what
what_can_you_do
Describe a task in plain language (any language) and get back exactly which tools on this server do it, with ready-to-run example calls — instead of reading the whole catalogue and guessing. Also returns multi-step recipes when a task needs several tools chained (invoices to a ledger, a bank statement reconciled, a messy CSV turned into a deliverable). Deterministic and free: it calls no model, costs nothing, and never runs out of quota. Call this FIRST when you are not sure what this server offers.
Endpoints
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://ainetcafe.com/mcp/table?s=registry | streamable-http | answering | 589 ms | 10 min ago |
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Netcafe Tables — questions
Answers built from our own checks of this server.
What can Netcafe Tables do?
It exposes 15 tools, read directly from the server on our last check. Among them: clean_table, csv_to_chart, csv_to_json, csv_to_md_table, csv_to_qbo, dedupe_entities and 9 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README.
How MCP servers expose tools in the first place →
What is Netcafe Tables mostly used for?
Its tools cluster around csv and xlsx. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is Netcafe Tables working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 687 ms. The bar chart above shows every period we have measured.
How do I connect Netcafe Tables?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Netcafe Tables need an API key?
No. Netcafe Tables completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 15 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Netcafe Tables?
It answers our handshake in 687 ms on average, which is faster than 21% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.
Is Netcafe Tables open source?
Yes — written in JavaScript, 1 stars on GitHub and 1 open issue. The source link is on this page, so you can read exactly what it does with your data before you connect it.