{"name":"com.ainetcafe/ai-netcafe","slug":"ainetcafe-ai-netcafe","title":null,"description":"Tables and ledgers checked by arithmetic, not by a model. 24 tools. MCP 2026-07-28 ready.","url":"https://mcp.market/server/ainetcafe-ai-netcafe","rating":null,"grade":"B","score":82,"certified":false,"status":"active","category":"ai","tags":["ai"],"presence":{"score":29,"stars":1,"forks":0,"downloads_week":44,"last_push_at":"2026-08-16T06:53:22.000Z","license":"MIT"},"uptime":{"percent":100,"checks":21,"ok":21,"last_checked_at":"2026-09-24T11:51:10.247Z","last_ok_at":"2026-09-24T11:51:10.247Z","latency_ms":766},"claimed":false,"transport":"mixed","callable_via_gateway":true,"default_price_micros":0,"repository":"https://github.com/mario03690/ai-netcafe","website":"https://ainetcafe.com/mcp.html","version":"1.7.0","remotes":[{"type":"streamable-http","url":"https://ainetcafe.com/mcp?s=registry"}],"packages":[{"registryType":"npm","registryBaseUrl":"https://registry.npmjs.org","identifier":"ai-netcafe","version":"1.2.1","runtimeHint":"npx","transport":{"type":"streamable-http","url":"https://ainetcafe.com/mcp?s=registry"}},{"registryType":"pypi","registryBaseUrl":"https://pypi.org","identifier":"ai-netcafe","version":"1.2.2","runtimeHint":"uvx","transport":{"type":"streamable-http","url":"https://ainetcafe.com/mcp?s=registry"}}],"tools":[{"name":"ai_visibility","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"url":{"type":"string","description":"Page to audit, e.g. https://example.com"}},"required":["url"]}},{"name":"ask_model","description":"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","write_action":true,"price_micros":0,"input_schema":{"type":"object","properties":{"prompt":{"type":"string","description":"The prompt to send."},"model":{"type":"string","description":"Model id. Call list_models for available ids. Defaults to a cheap capable model."},"system":{"type":"string","description":"Optional system instruction."},"max_tokens":{"type":"integer","description":"Optional output cap."}},"required":["prompt"]}},{"name":"build_app","description":"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","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"description":{"type":"string","description":"What the tool should do, in any language. Be specific about inputs/outputs."},"name":{"type":"string","description":"Optional short app name (defaults to the description)."},"visibility":{"type":"string","description":"\"public\" (default, listed in the store) or \"unlisted\" (URL-only, not in the store)."},"refine":{"type":"string","description":"Slug of an app you built earlier (e.g. \"u-1a23e679\") to modify instead of building from scratch — describe only the change in `description`."}},"required":["description"]}},{"name":"check_job","description":"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>","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"job_id":{"type":"string","description":"The job_id returned when the task was started."}},"required":["job_id"]}},{"name":"china_reachability","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"url":{"type":"string","description":"Full URL to test, e.g. https://example.com"}},"required":["url"]}},{"name":"clean_table","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"url":{"type":"string","description":"Link to the CSV. Provide this or text."},"text":{"type":"string","description":"The CSV content itself. Provide this or url."},"ops":{"type":"string","description":"Comma-separated, default \"dedupe,trim,drop_empty,unify_blank\". Also available: split_column, transpose (swap rows/columns), wide_to_long (unpivot a wide table into the long format analysis tools expect)."},"keep":{"type":"string","description":"For wide_to_long: comma-separated id columns to keep as-is. Defaults to the first column."},"split_column":{"type":"string","description":"Column name to split (requires ops to include split_column)."},"split_by":{"type":"string","description":"Separator to split on, default a single space."}}}},{"name":"compare_models","description":"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","write_action":true,"price_micros":0,"input_schema":{"type":"object","properties":{"prompt":{"type":"string","description":"The prompt to send to every model."},"models":{"type":"array","items":{"type":"string"},"description":"Model ids to compare (2-5). Defaults to a cheap/mid/strong spread."},"system":{"type":"string","description":"Optional system instruction applied to all."}},"required":["prompt"]}},{"name":"create_task","description":"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.","write_action":true,"price_micros":0,"input_schema":{"type":"object","properties":{"kind":{"type":"string","description":"watch_page | daily_answer | watch_reachability | pipeline"},"input":{"type":"string","description":"The URL to watch, or the question to re-research."},"interval_seconds":{"type":"integer","description":"How often to run. Minimum 900 (15 min), default 3600."},"notify_url":{"type":"string","description":"Optional https webhook to POST results to when they change."}},"required":["kind","input"]}},{"name":"delete_task","description":"Stop and remove a scheduled task and its run history.","write_action":true,"price_micros":0,"input_schema":{"type":"object","properties":{"task_id":{"type":"integer","description":"From list_tasks."}},"required":["task_id"]}},{"name":"diff_tables","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"url_a":{"type":"string","description":"Link to the first CSV."},"url_b":{"type":"string","description":"Link to the second CSV."},"text_a":{"type":"string","description":"Or the first CSV content directly."},"text_b":{"type":"string","description":"Or the second CSV content directly."},"key":{"type":"string","description":"Column that identifies a row, e.g. id."}},"required":["key"]}},{"name":"diff_text","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"a":{"type":"string","description":"The first (before) text."},"b":{"type":"string","description":"The second (after) text."}},"required":["a","b"]}},{"name":"extract_invoices","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"urls":{"type":"string","description":"Invoice URLs — comma-separated, or pass an array. Up to 20 per call."}},"required":["urls"]}},{"name":"extract_statement","description":"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).","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"url":{"type":"string","description":"Public URL of the statement PDF."}},"required":["url"]}},{"name":"extract_tables","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"url":{"type":"string","description":"Public URL of the PDF."},"fields":{"type":"string","description":"Optional comma-separated target columns, e.g. \"invoice_no,supplier,date,amount\". Omit to infer from the header."}},"required":["url"]}},{"name":"fetch_page","description":"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","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"url":{"type":"string","description":"The page URL to fetch."}},"required":["url"]}},{"name":"get_app","description":"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>","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"slug":{"type":"string","description":"Application slug, from list_apps."}},"required":["slug"]}},{"name":"get_task_runs","description":"Recent runs of one scheduled task: what it returned, whether the result changed, and measured platform cost metadata. User charge is $0.00.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"task_id":{"type":"integer","description":"From create_task or list_tasks."},"limit":{"type":"integer","description":"How many recent runs, max 20, default 5."}},"required":["task_id"]}},{"name":"json_yaml","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"text":{"type":"string","description":"The JSON or YAML content."},"to":{"type":"string","description":"Optional: \"json\" or \"yaml\" to force the direction."}},"required":["text"]}},{"name":"jwt_decode","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"token":{"type":"string","description":"The JWT string."}},"required":["token"]}},{"name":"list_apps","description":"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","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"category":{"type":"string","description":"Optional filter, e.g. \"office\", \"research\", \"chat\"."}}}},{"name":"list_models","description":"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","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"tier":{"type":"string","enum":["free","premium"],"description":"Optional reference tier filter. All currently healthy tiers are available without a user key during the beta."}}}},{"name":"list_tasks","description":"Show scheduled tasks, next run times, run counts, and measured platform cost metadata. User charge is $0.00 during the beta.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{},"required":[]}},{"name":"merge_tables","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"urls":{"type":"string","description":"Comma-separated CSV links, at least two."},"texts":{"type":"array","items":{"type":"string"},"description":"Or pass the CSV contents directly as an array."}}}},{"name":"model_costs","description":"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","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"days":{"type":"integer","description":"Measurement window in days (default 30)."}}}},{"name":"pdf_to_markdown","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"url":{"type":"string","description":"Public URL of the PDF, or of a page image (png/jpg) for scanned documents."}},"required":["url"]}},{"name":"recall","description":"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)","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"query":{"type":"string","description":"Optional search terms; omit to list the most recent."},"project":{"type":"string","description":"Optional project filter."},"limit":{"type":"integer","description":"Max results (default 8, up to 20)."}}}},{"name":"reconcile_ledger","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"url_a":{"type":"string","description":"Link to side A (e.g. your books)."},"url_b":{"type":"string","description":"Link to side B (e.g. the statement)."},"text_a":{"type":"string","description":"Or the CSV content of side A directly."},"text_b":{"type":"string","description":"Or the CSV content of side B directly."},"key":{"type":"string","description":"Column name to match rows on, e.g. order_id."},"amount":{"type":"string","description":"Numeric column to compare, e.g. amount."}},"required":["key","amount"]}},{"name":"regex_test","description":"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.","write_action":true,"price_micros":0,"input_schema":{"type":"object","properties":{"pattern":{"type":"string","description":"The regular expression, without surrounding slashes."},"text":{"type":"string","description":"The text to test against."},"flags":{"type":"string","description":"Optional flags, e.g. \"gi\". Default \"g\"."}},"required":["pattern","text"]}},{"name":"remember","description":"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\"}","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"content":{"type":"string","description":"The memory itself, self-contained (≤2000 chars)."},"kind":{"type":"string","enum":["decision","preference","bugfix","discovery","note"],"description":"Category; default \"note\"."},"project":{"type":"string","description":"Optional project name to scope recall later."}},"required":["content"]}},{"name":"render_diagram","description":"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\"","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"source":{"type":"string","description":"The diagram source code (e.g. a Mermaid flowchart)."},"type":{"type":"string","description":"Diagram language: mermaid (default), plantuml, graphviz, c4plantuml, excalidraw, blockdiag, erd…"},"format":{"type":"string","description":"\"svg\" (default) or \"png\"."}},"required":["source"]}},{"name":"transpile_sql","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"sql":{"type":"string","description":"The SQL statement (or several, separated by semicolons)."},"read":{"type":"string","description":"Source dialect, e.g. \"mysql\". Omit to auto-detect from generic SQL."},"write":{"type":"string","description":"Target dialect, e.g. \"postgres\", \"bigquery\", \"doris\"."}},"required":["sql","write"]}},{"name":"validate_json","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"text":{"type":"string","description":"The JSON to validate."},"schema":{"type":"string","description":"Optional JSON Schema (as JSON text) — required[] and properties[].type are checked."}},"required":["text"]}},{"name":"web_search","description":"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","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"query":{"type":"string","description":"The search query."},"max_results":{"type":"integer","description":"Max results (default 8, up to 20)."}},"required":["query"]}},{"name":"what_can_you_do","description":"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.","write_action":false,"price_micros":0,"input_schema":{"type":"object","properties":{"task":{"type":"string","description":"What you are trying to do, e.g. \"reconcile a bank statement against my books\" or \"把一堆发票整理成能入账的表格\""}},"required":["task"]}}],"scan":{"score":82,"grade":"B","scanned_at":"2026-09-23T11:54:48.955Z","report":{"scannerVersion":"0.1.9","scannedAt":"2026-09-23T11:54:48.959Z","components":{"code":{"score":25,"max":25,"notes":["2 source files scanned","4 source files scanned"]},"reliability":{"score":20,"max":20,"notes":["remote reachable in 1368ms"]},"poisoning":{"score":15,"max":15,"notes":["34 tool descriptions checked"]},"auth":{"score":3,"max":15,"notes":["open endpoint exposes 5 write-action tools with no auth"]},"maintenance":{"score":12,"max":15,"notes":["last push 38 days ago"]},"identity":{"score":7,"max":10,"notes":["namespace and repository owner differ","GitHub account older than a year","website matches verified namespace"]}},"findings":[{"id":"auth.open-write","severity":"high","component":"auth","title":"Write-action tools reachable without authentication"}],"inputs":{"probes":[{"url":"https://ainetcafe.com/mcp?s=registry","reachable":true,"authRequired":false,"latencyMs":1368,"serverInfo":{"name":"ai-netcafe","version":"1.5.0"}}],"packages":[{"registryType":"npm","identifier":"ai-netcafe","version":"1.2.1","found":true,"license":"MIT","hasInstallScripts":false,"dependencyCount":0,"publishedAt":"2026-08-07T02:25:42.749Z","repositoryUrl":"git+https://github.com/mario03690/ai-netcafe.git","weeklyDownloads":44},{"registryType":"pypi","identifier":"ai-netcafe","version":"1.2.2","found":true,"license":"MIT","dependencyCount":0,"publishedAt":"2026-08-07T02:25:38.967002Z","repositoryUrl":"https://github.com/mario03690/netcafe-sdk"}],"repo":{"found":true,"owner":"mario03690","repo":"ai-netcafe","archived":false,"pushedAt":"2026-08-16T06:53:22Z","stars":1,"forks":0,"openIssues":1,"ownerType":"User","ownerAvatarUrl":"https://avatars.githubusercontent.com/u/79393843?v=4","ownerCreatedAt":"2021-02-21T06:22:05Z"},"icon":{"url":null,"source":"none"},"presence":{"stars":1,"forks":0,"downloadsWeek":44,"license":"MIT","lastPushAt":"2026-08-16T06:53:22.000Z","score":29}}}},"grade_history":[],"reviews":[]}