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Lantern Works GPU Prices: daily GPU rental price comparison MCP Server

by connormatthewdouglas Your server? Claim it
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Lantern Works GPU Prices: daily GPU rental price comparison is answering right now. Last checked 13 min ago. 18 883 installs a week from pypi. It exposes 12 tools. Last commit 1 Nov 2026.

GPU rental prices checked daily, with price history and change feed; stack optimizer; AI-infra deals

Installs per day peak 8 569 · avg 629
a month agotoday
Uptime history 68 hours of history
68 hours agonow
100.0%
Uptime 24h
92 of 92 checks
12
Tools
read from the server
1404 ms
Response time
average over 24h
18 883
Installs / week
npm and PyPI

What changed 35

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 30 October 2026. No other catalogue keeps this.

30 Oct a tool changed version19 times that day
30 Oct 9 tools changed the parameters they ask for11 times that day compare_deals, compare_gpu_prices, estimate_job_cost and 6 more
30 Oct 3 tool descriptions were rewritten5 times that day compare_gpu_prices, optimize_agent_stack, watch_price
and 22 more, back to 30 October 2026

What the code does

We read the source, 21 h 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.

    $("res").innerHTML=h;document.dispatchEvent(new CustomEvent("lw:event",{detail:"stack"}))}
Page loads a third-party script embed/index.html:151
  <script async src="https://thelanternworks.com/embed/badge.js"></script>

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.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 13 min ago.

run in your terminal
claude mcp add lantern-works-deals --transport http 'https://lantern-works-mcp.lantern-works.workers.dev/mcp?ref=mcp-registry'
Settings → Connectors → Add custom connector, then paste this address
https://lantern-works-mcp.lantern-works.workers.dev/mcp?ref=mcp-registry
~/.codex/config.toml
[mcp_servers.lantern-works-deals]
url = "https://lantern-works-mcp.lantern-works.workers.dev/mcp?ref=mcp-registry"
.cursor/mcp.json
{
  "mcpServers": {
    "lantern-works-deals": {
      "url": "https://lantern-works-mcp.lantern-works.workers.dev/mcp?ref=mcp-registry"
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "lantern-works-deals": {
      "type": "http",
      "url": "https://lantern-works-mcp.lantern-works.workers.dev/mcp?ref=mcp-registry"
    }
  }
}

Available tools 12

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

watch
create_watch_key
Hosted only, free, opt-in. Register a webhook for GPU price alerts and get an api_key plus a webhook signing secret (both shown ONCE; store them). webhook_url must be public https. email is optional contact only (no mail is sent). No payment. Stored: a hash of the key, the webhook URL, optional email, your watches and per-key counts.
delete_watch
Hosted only. Delete one of your watches by watch_id.
watch_price
Hosted only. Alert your webhook (signed POST) after the daily refresh when a tracked rate for `gpu` crosses at or below max_hourly_usd, or a change of a watched kind (down/up/new; default down) lands at or below it. Only ELIGIBLE rates match (same contract as compare/estimate): every word of gpu must match the model; 'A100 80GB' or vram_gb=80 never matches a 40GB row; tiers (on-demand, community, marketplace, interruptible/spot, dedicated-monthly, reserved; default all but reserved) never matches another class; a row confirmed sold out never matches (in_stock='require' also skips unknown stock). region: code from availability.available_regions; a rate with no unexpired region evidence stays unresolved and never matches. Each event is delivered at most once per watch (dedupe on event_id). Pass api_key or an Authorization: Bearer header.
compare
compare_deals
Compare 2-5 deals side by side (price, unit, offer type, code, verification), best value first.
compare_gpu_prices
Compare tracked GPU rental prices for one model (e.g. 'H100', 'A100 SXM', 'RTX 4090', 'L40S'), cheapest first. If a result looks wrong, give the user its report_issue_url. Same data as https://thelanternworks.com/api/v1/gpu-prices.json. Sorted by hourly_usd ascending; each result has source_url and checked_at. 'Cheapest' means cheapest among tracked providers, not the whole market. limit 1-25. Unknown model returns not_found listing tracked models. Each result has tier_class: on-demand | community | marketplace | interruptible (spot/preemptible) | reserved | dedicated-monthly. Reserved (reservation/commitment 'starting from') rates are left out unless include_reserved=true, and even then they are never reported as cheapest. The cheapest overall can be spot or community capacity; on_demand_only=true keeps only on-demand rates, and the summary names the cheapest on-demand rate when the overall cheapest isn't. include_history=true adds each result's price_history (daily-snapshot change points) and history.recent_changes (price changes for this model among tracked providers, last 30 days) from /api/v1/gpu-prices/history.json. Each result has data_age_hours (hours since its price was last verified), degraded (> 48 h) and stale (> 7 days). By default a rate whose price is older than 168 h is never ranked or named cheapest: it is listed in stale_prices ('stale price (N days old)'); if every rate is stale, results is empty and the summary says no current cheapest. max_data_age_hours (optional) replaces the 168 h default and drops older rates; excluded_too_old counts them. region (optional): a country/area code ('US', 'EU') matches every published zone in it; a zone code ('US-NE-1', 'us-east-1') matches exactly, any case. Rates whose unexpired published regions exclude it are dropped; rates with no region evidence stay, labelled unresolved and ranked after the rest. Each result has eligibility {eligible, applied, unmet, unknown} from the shared T47 contract; constraints.eligible_rate_ids is the same set estimate_job_cost and price watches use. Unknown stock is not confirmed availability.
optimize
optimize_agent_stack
Estimate a monthly stack cost from a short description of the agent being built. description: free text, e.g. 'scrapes 20k JS pages/month via 5 GB residential proxies, 3k search queries, summarizes with an LLM, budget $300/mo'. Parsed deterministically (keywords/regex, no LLM) into components: gpu, scraping, proxy, search, llm_api, email, hosting, database, monitoring. Optional fields override the parse: gpu_hours (GPU-hours/month), gpu_model ('H100', 'A100', 'RTX 4090'), model_size_b (billions of params; sets a minimum VRAM using FP16 x 1.2), scrape_pages, js_rendering, proxy_gb, search_queries, emails_sent, llm_api, monthly_budget_usd. Each component gets the cheapest option with a cited price among tracked providers, with calc, source_url, verified_at, referral_disclosure (set when the link is a referral link) and manual-signup notes. Components with no cited price say 'no sourced price tracked' (nothing is estimated). Totals show the math and say whether they are complete. Pulled listings are excluded. Every option has data_age_hours, degraded (> 48 h) and stale (> 7 days); GPU prices older than 168 h never rank by default (listed in the line's stale_prices); max_data_age_hours replaces that default and drops older options (excluded_too_old counts them). Same data as optimize_stack, compare_gpu_prices and the deal feed.
optimize_stack
Cheapest suitable stack among tracked providers for monthly needs (set the quantities you need, rest 0). scrape_pages: pages/month without JS rendering. scrape_pages_js: pages/month needing JS rendering. proxy_gb: residential proxy GB/month. emails_sent: transactional emails/month. search_queries: search API queries/month. gpu_hours: GPU-hours/month (1 GPU), optionally gpu_model e.g. 'H100', 'A100', 'RTX 4090'. Each line has the chosen plan, monthly_cost_usd, calc, vendor quote, source_url, checked_at and assumptions, plus alternatives. A vendor price that isn't published is 'unknown' (never estimated). manual_signup_only=true means a human must sign up (never automate it); exclude_manual_signup=true drops those plans. Same data as https://thelanternworks.com/api/v1/stack-pricing.json and /tools/stack-optimizer/.
deal
get_deal
Get one deal's public record by id, including redeem_url and agent_instructions.
deals
search_deals
Search agent work-stack deals (compute, search, email, unblock, hosting...). offer_type: verified_discount | listed_discount (not confirmed; verified_at null) | free_tier | trial | standard_referral | credit_only_referral. max_price excludes deals with unknown price. limit 1-25. Pass next_cursor back as cursor to page.
estimate
estimate_job_cost
Cost of one GPU job (not cost per hour) among tracked providers, cheapest compute subtotal first. You supply the duration: job_hours, OR work_units plus throughput_units_per_gpu_hour from your own benchmark (job_hours = work_units / (throughput x gpus_per_job)). If you give workload + work_units but no throughput, a directly applicable published figure (closed-division MLPerf Inference, exact GPU variant, inference only) is used: throughput_basis='published_benchmark' with throughput_source {url, quote, date, benchmark, derived, caveats}; your throughput always wins. Otherwise not_found 'missing: throughput for {gpu}'. Whole-instance billing: instances = ceil(gpus_per_job / gpus_per_instance), all allocated GPUs billed (9 GPUs on an 8-GPU-only offer bill 16). Reserved and held-stale rates are never ranked; spot/interruptible only if allow_interruptible. Each result has rate_id, source_url, verified_at, data_age_hours/degraded/stale. Response has assumptions, citations, missing_costs, budget_verdict (unresolved: extras unknown) and a quote_id. Compute subtotal only.
price
get_price_changes
GPU rental price changes among tracked providers, each with old/new hourly price, change_pct, direction, the vendor source_url, a stable event_id (dedupe key) and rate_id. since: 'YYYY-MM-DD' returns every change on or after that date, newest first (daily snapshots in /api/v1/gpu-prices/history.json); omitted returns the latest day's moves (/api/v1/gpu-price-changes.json). cursor: pass next_cursor from a previous call to get every change after it, oldest first, with has_more; loop until has_more is false, and store next_cursor only after processing (a watcher never misses or repeats events). error cursor_expired means re-sync with since and dedupe by event_id. kinds: optional subset of down, up, new, removed, same. gpu: optional model filter (substring, e.g. 'H100'). limit 1-200. Includes data_checked_at and next_refresh_utc (prices refresh daily at about 10:23 UTC).
watches
list_watches
Hosted only. Your watches and per-key alert counts.

Endpoints

URLTransportStateLatencyChecked
https://lantern-works-mcp.lantern-works.workers.dev/mcp?ref=mcp-registry streamable-http answering 1875 ms 13 min ago

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Lantern Works GPU Prices: daily GPU rental price comparison — questions

Answers built from our own checks of this server.

What can Lantern Works GPU Prices: daily GPU rental price comparison do?
It exposes 12 tools, read directly from the server on our last check. Among them: compare_deals, compare_gpu_prices, create_watch_key, delete_watch, estimate_job_cost, get_deal and 6 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 Lantern Works GPU Prices: daily GPU rental price comparison mostly used for?
Its tools cluster around watch, compare and optimize. 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 Lantern Works GPU Prices: daily GPU rental price comparison working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 92 of 92 checks got a reply (100.0%), average response time 1404 ms. The bar chart above shows every period we have measured.
How do I connect Lantern Works GPU Prices: daily GPU rental price comparison?
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 Lantern Works GPU Prices: daily GPU rental price comparison need an API key?
No. Lantern Works GPU Prices: daily GPU rental price comparison completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 12 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Lantern Works GPU Prices: daily GPU rental price comparison?
It answers our handshake in 1404 ms on average, which is faster than 1% 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 Lantern Works GPU Prices: daily GPU rental price comparison?
The pypi package lantern-works-deals-mcp was installed 18 883 times in the last week. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.
Is Lantern Works GPU Prices: daily GPU rental price comparison open source?
The code is open source: it is published under the MIT licence, written in HTML, 1 stars on GitHub and 3 open issues. The licence covers the code in the repository, not the hosted service at lantern-works-mcp.lantern-works.workers.dev, which runs on its operator's own terms.