AI Netcafe MCP Server

by ainetcafe Your server? Claim it

answering

AI Netcafe is answering right now. Last checked 14 min ago. 254 installs a week from pypi. It exposes 34 tools. Last commit 16 Aug 2026.

Tables and ledgers checked by arithmetic, not by a model. 24 tools. MCP 2026-07-28 ready.

Installs per day peak 28 · avg 10 · -45% w/w

a month agotoday

Uptime history 91 days of history · worst day 0%

91 days agonow

93.4%

Uptime 24h

170 of 182 checks

Tools

read from the server

710 ms

Response time

average over 24h

254

Installs / week

npm and PyPI

What changed 120

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 12 August 2026. No other catalogue keeps this.

11 Sep 9 tool descriptions were rewritten11 times that day ask_model, compare_models, create_task and 6 more

11 Sep a tool changed the parameters it asks for list_models

8 Sep 9 tool descriptions were rewritten ask_model, compare_models, create_task and 6 more

8 Sep a tool changed the parameters it asks for list_models

1 Sep a tool description was rewritten fetch_page

29 Aug 8 tool descriptions were rewritten ask_model, compare_models, create_task and 5 more

29 Aug a tool changed the parameters it asks for list_models

20 Aug a tool description was rewritten create_task

20 Aug a tool changed the parameters it asks for create_task

16 Aug a tool description was rewritten what_can_you_do

and 87 more, back to 12 August 2026

What the code does

We read the source, 1 d ago · tools taken from the live server · rules 995398eba69f

Capabilities

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

File ships in the package but is absent from the source [пакет] src/ai_netcafe/__init__.py:1, [пакет] src/ai_netcafe/cli.py:1, [пакет] src/ai_netcafe/client.py:1

этот файл ставится пользователю, но в репозитории его нет

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

This code can reach further than it looks

We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 14 min ago.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add ai-netcafe --transport http https://ainetcafe.com/mcp

Settings → Connectors → Add custom connector, then paste this address

https://ainetcafe.com/mcp

~/.codex/config.toml

[mcp_servers.ai-netcafe]
url = "https://ainetcafe.com/mcp"

.cursor/mcp.json

{
  "mcpServers": {
    "ai-netcafe": {
      "url": "https://ainetcafe.com/mcp"
    }
  }
}

.vscode/mcp.json

{
  "servers": {
    "ai-netcafe": {
      "type": "http",
      "url": "https://ainetcafe.com/mcp"
    }
  }
}

This server publishes 1 more address. The block above uses the one we reach during checks; the full list is under Endpoints below, and the author may intend a particular one for your client.

Available tools 34

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

extract

extract_invoices

Give it up to 20 invoice URLs (PDF or page images) and get back one table ready to post: number, date, seller, buyer, net / tax / gross, currency. Every row is checked in code — net + tax must equal gross — and the batch total is re-added independently, so a row the model misread is flagged with the exact difference instead of quietly landing in your books. Mixed currencies get no batch total on purpose: adding them together would be an accounting error. CSV is UTF-8 with BOM so Excel opens it right.

extract_statement

Turn a bank statement or transaction PDF into a clean transaction table (JSON + CSV), then cross-check it: opening + credits - debits must equal the stated closing balance. If it does not balance you get the exact difference and which row the running balance first breaks at — so you know whether the table is safe to use for accounting. Text-layer PDFs only (scanned images not yet supported).

extract_tables

Extract tables from a PDF into structured rows (JSON + CSV). Pass fields to force a fixed set of columns — that aligns a pile of documents that each name their headers differently into one consistent table. Rows the model was unsure about are flagged rather than guessed. Text-layer PDFs only.

task

create_task

Create a task that runs on a schedule in our cloud — you do not keep anything running. It only notifies you when the result actually changes. Kinds: watch_page (Watch a web page and report when its content changes); daily_answer (Re-run a web-researched question on a schedule and report when the answer changes); watch_reachability (Track whether a site stays reachable from mainland China); pipeline (Run one of your production lines (create_pipeline) on a schedule; every run leaves a proof-carrying work order). Needs a workspace token (?w=ws_... on your MCP URL) so you can manage it later. Application and model calls are subsidized during the free beta; your charge is $0.00 and capacity limits apply.

delete_task

Stop and remove a scheduled task and its run history.

get_task_runs

Recent runs of one scheduled task: what it returned, whether the result changed, and measured platform cost metadata. User charge is $0.00.

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.

diff_text

Returns which lines were added and which were removed, with line numbers — computed with a longest-common-subsequence, not guessed by a model. Use to compare two versions of a config, a document, or any command output, instead of asking an LLM to eyeball two blobs and hoping it notices.

app

get_app

Full details of one hosted application: what it does, how to use it, measured benchmark scores, source repository, and the URL a human can open to run it. Example — GET https://ainetcafe.com/t/get_app?slug=<slug-from-list_apps>

apps

list_apps

List the open-source AI applications hosted and ready to run at AI NetCafé (ainetcafe.com). Each one normally requires local setup (Docker/Python + your own model API key); here they run pre-configured. Use this to find a tool for a task like translating a PDF with formulas intact, generating a PowerPoint file, polishing an academic paper, or running an autonomous research report. Do not call this first when the request already clearly matches compare_models, translate_pdf, deep_research, or make_slides; call that task tool directly. Example — GET https://ainetcafe.com/t/list_apps

ask

ask_model

Send a prompt to one specific large language model and get the answer plus measured platform cost metadata. The beta platform covers the user charge ($0.00); capacity limits still apply. Example — GET https://ainetcafe.com/t/ask_model?prompt=Say+hi&model=deepseek-v4-flash

build

build_app

Turn one plain-language description into a LIVE single-page web tool: code is generated, deployed to managed hosting with HTTPS, and listed — you get the public URL in ~1-2 minutes. Best for tool-style apps: calculators, converters, checklists, timers, generators, small games. Async — poll with check_job. Example — tools/call build_app {"description":"a tip calculator web app"} → poll check_job

china

china_reachability

Fetch a URL from a real mainland-China network egress and report HTTP status, latency and China DNS resolution. Answers "is my site/API usable from China?" with a measurement instead of a guess — you cannot get this from a VPS abroad.

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.

compare

compare_models

Run one prompt across multiple LLMs in parallel and return every answer side by side with measured platform cost metadata and latency. The beta platform covers the user charge ($0.00). This answers "which model should I actually use for this kind of task?" with data instead of guesswork. Example — GET https://ainetcafe.com/t/compare_models?prompt=Explain+CAP+theorem+in+1+line

job

check_job

Get the status or result of a job started by deep_research, translate_pdf, or make_slides. Poll every 15-30 seconds until status is "done" or "error". While work is pending, follow retry_after_seconds and next_action; when complete, prefer structured_result when present. Example — GET https://ainetcafe.com/t/check_job?job_id=<id-from-a-job-tool>

json

json_yaml

Converts JSON to YAML or YAML to JSON. It works out which one you gave it, so you do not have to say. A parse failure comes back with the parser message instead of silently producing something that looks fine and is not. Use when a config, a CI file, or a Kubernetes manifest needs to be in the other format.

jwt

jwt_decode

Decodes the header and payload of a JWT and reports issued-at / expiry as readable timestamps plus seconds remaining. The signature is NOT verified and the response says so — decoding is fine for debugging a token you already hold, but never treat these values as proof of anything; verification needs the secret and belongs in your own service.

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.

model

model_costs

Measured platform cost metadata for one call on each model; your charge is $0.00 during the free beta. Vendors publish per-million-token list prices, but a call's cost depends on how many tokens the model chooses to emit — models differ by an order of magnitude on the same prompt. standard_bench sends an IDENTICAL prompt to every model, so the difference is the model, not the workload — use that to choose a model before bulk work. production_mixed is real traffic and is NOT comparable across models. Free to cite, CC BY 4.0. Example — GET https://ainetcafe.com/t/model_costs

models

list_models

List every model currently available in the free beta with reference input/output rates and health metadata. Those rates are platform cost metadata only; every user charge is $0.00 during the beta. Example — GET https://ainetcafe.com/t/list_models

page

fetch_page

Fetch a public URL and return clean LLM-ready Markdown from the server-rendered response. This tool does not execute browser JavaScript; for SPA or empty-text pages, use web_search, a browser, or the site's API. Use it after web_search to read a reachable public source, or to ingest a static page for analysis. Example — GET https://ainetcafe.com/t/fetch_page?url=https://example.com

pdf

pdf_to_markdown

Convert a PDF (or a scanned page image) into clean Markdown that keeps headings, lists and tables, and puts multi-column pages in the right reading order. Text-layer PDFs are read exactly and cost far less; images go through a vision model.

recall

recall

Retrieve previously stored memories, optionally filtered by search query and/or project. Call at the start of work on a known project to restore context: why decisions were made, known fixes, preferences. Example — GET https://ainetcafe.com/t/recall?query=<what+to+remember> (needs a workspace/key for durable memory)

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.

regex

regex_test

Runs a regular expression against sample text and returns every match with its position and capture groups (named groups included). Use before wiring a pattern into code, instead of guessing whether the escaping survived the trip through JSON and the shell.

remember

remember

Persist a durable memory: an architecture decision, a stable user preference, a verified bug fix, or an important discovery. The free beta provides a bounded per-caller/workspace memory pool; no personal API key is required. Do not store secrets or raw logs. Example — tools/call remember {"content":"Deploy key rotates monthly"}

render

render_diagram

Turn diagram-as-code into an image: Mermaid, PlantUML, Graphviz/DOT, C4, Excalidraw and 20+ more (self-hosted Kroki). Returns a hosted SVG/PNG URL you can embed directly in Markdown or HTML. Example — GET "https://ainetcafe.com/t/render_diagram?source=graph TD;A--%3EB&format=png"

tasks

list_tasks

Show scheduled tasks, next run times, run counts, and measured platform cost metadata. User charge is $0.00 during the beta.

transpile

transpile_sql

Convert a SQL statement from one dialect to another — mysql, postgres, sqlite, tsql, oracle, snowflake, bigquery, redshift, spark, hive, presto, trino, duckdb, clickhouse, databricks, doris, starrocks and more. Deterministic parser (sqlglot), not an LLM: the same input always produces the same output, and syntax errors come back with the exact line and column. Use it when migrating queries between databases or debugging dialect-specific syntax.

validate

validate_json

Checks that text parses as JSON, and optionally that required keys are present with the right top-level types. Returns the specific violations, not just true/false. Checks required + types only — not full JSON Schema, and it says so rather than pretending. Use before feeding generated JSON into something that will fail on it.

visibility

ai_visibility

Audit a URL for AI visibility: which AI crawlers robots.txt actually allows (parsed per user-agent group, not keyword-matched), whether llms.txt / sitemap / JSON-LD / canonical exist, and how much real text an agent gets without running JavaScript. Returns a score plus the specific fixes, ordered by impact.

web

web_search

Search the live web through a self-hosted SearXNG meta-search (aggregates dozens of engines, no tracking). Returns titles, URLs and snippets. Use when you need current information or sources. Example — GET https://ainetcafe.com/t/web_search?query=latest+MCP+spec

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.

Tools removed

Tools this server used to expose. Anything built against them stopped working on the day they went.

check_grammar

removed 13 Aug 2026

check_vulns

removed 13 Aug 2026

convert_to_pdf

removed 13 Aug 2026

csv_to_qbo

removed 13 Aug 2026

deep_research

removed 13 Aug 2026

fix_csv_encoding

removed 13 Aug 2026

forget

removed 13 Aug 2026

get_weather

removed 13 Aug 2026

make_badge

removed 13 Aug 2026

make_chart

removed 13 Aug 2026

make_qr

removed 13 Aug 2026

make_slides

removed 13 Aug 2026

package_info

removed 13 Aug 2026

pdf_add_page_numbers

removed 13 Aug 2026

project_status

removed 13 Aug 2026

redact_text

removed 13 Aug 2026

split_spritesheet

removed 13 Aug 2026

submit_project

removed 13 Aug 2026

text_to_image

removed 13 Aug 2026

transcribe_audio

removed 13 Aug 2026

translate_i18n_json

removed 13 Aug 2026

translate_pdf

removed 13 Aug 2026

translate_srt

removed 13 Aug 2026

translate_text

removed 13 Aug 2026

Endpoints

URL	Transport	State	Latency	Checked
https://ainetcafe.com/mcp	streamable-http	answering	958 ms	14 min ago
https://ainetcafe.com/mcp?s=registry	streamable-http	answering	593 ms	14 min ago

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AI Netcafe — questions

Answers built from our own checks of this server.

What can AI Netcafe do?

It exposes 34 tools, read directly from the server on our last check. Among them: ai_visibility, ask_model, build_app, check_job, china_reachability, clean_table and 28 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 AI Netcafe mostly used for?

Its tools cluster around task, extract and diff. 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 AI Netcafe working right now?

We send a real MCP handshake every 15 minutes. Over the last 24 hours 170 of 182 checks got a reply (93.4%), average response time 710 ms. The bar chart above shows every period we have measured.

Did AI Netcafe ever remove tools?

Yes. check_grammar, check_vulns, convert_to_pdf, csv_to_qbo and 20 more are no longer exposed — we recorded the date each one disappeared. A tool vanishing usually means a breaking change for anything that depended on it.

How do I connect AI Netcafe?

Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.

Does AI Netcafe need an API key?

No. AI Netcafe completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 34 of them are readable on this page. This is what we observed, not what the docs claim.

How fast is AI Netcafe?

It answers our handshake in 710 ms on average, which is faster than 12% 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.

How many people use AI Netcafe?

The npm package ai-netcafe was installed 254 times in the last week. Week over week that is -45%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.

Is AI Netcafe open source?

We cannot say either way: written in JavaScript, 1 stars on GitHub and 1 open issue, but we could not determine the licence, and without one the code is not open source by default.