pricing-time-machine-mcp
Provides historical pricing analysis for ClickUp by reading archived ClickUp pricing pages from the Wayback Machine, extracting plan names, prices, billing periods, and changes over time.
Provides historical pricing analysis for Coda by reading archived Coda pricing pages from the Wayback Machine, extracting plan names, prices, billing periods, and changes over time.
Provides historical pricing lookups for Figma from archived Figma pricing pages, such as retrieving what Figma charged for Professional in a given year.
Provides pricing history reports for Linear from archived linear.app/pricing pages, extracting plan and price changes over time.
Provides historical pricing analysis for Notion by reading archived Notion pricing pages and extracting plans, prices, billing periods, and changes such as dropped free tiers or renamed plans.
Enables timeline and comparison analysis of Slack's pricing changes from archived Slack pricing pages, including price increases over time.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@pricing-time-machine-mcp How did Notion's pricing change since 2022?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
pricing-time-machine-mcp
See how any SaaS pricing page changed over the years. An MCP server that reads archived copies of pricing pages from the Wayback Machine and pulls out the plans and prices, so Claude (or any MCP client) can tell you when a competitor raised prices, renamed plans or dropped a free tier.
No API keys. No scraping of live sites. One line to install.
You: How did Notion's pricing change since 2022?
Claude: [compare_pricing → notion.so/pricing, 2022-03 vs latest]
• Personal Pro ($4/mo billed yearly) is gone; the cheapest paid plan is now
Plus at $10 per member/month.
• Team ($8/user/mo) became Business at $20 per member/month: 2.5×.
• Free is still $0.Summarized from real tool output: archived copies of 31 Mar 2022 and 7 Sep 2026.

Why
You want to know | Without it | With pricing-time-machine |
When a competitor raised prices | Click through dozens of Wayback snapshots by hand |
|
What their plans looked like in 2021 | Find a snapshot, read the page |
|
How a whole market moved | Days of spreadsheet work |
|
Related MCP server: CostBench MCP Server
How it works
flowchart LR
C[Claude / MCP client] -->|tool call| S[pricing-time-machine-mcp]
S --> I[Wayback CDX index: which months were archived]
S --> W[Archived page closest to a date]
W --> X[Extract prices: amount, currency, /mo /yr, per user, plan guess, context]
X -->|compact table + page text around prices| CThe server does the deterministic part (finding snapshots, extracting prices, grouping periods). The model does the interpretation: which price belongs to which plan and what a change means. Archived pages never change, so they are cached on disk (~/.cache/pricing-time-machine).
Install
Requires uv.
Claude Code
claude mcp add pricing-time-machine -- uvx pricing-time-machine-mcpClaude Desktop / Cursor (claude_desktop_config.json / .cursor/mcp.json)
{
"mcpServers": {
"pricing-time-machine": {
"command": "uvx",
"args": ["pricing-time-machine-mcp"]
}
}
}Tools
Tool | What it does |
| Reads N archived copies across the years, groups identical prices into periods, lists what was added/removed |
| Prices on the page closest to a date, with plan guess, billing hints, context and the page text around them |
| One page at two dates: both price tables plus added/removed prices |
| 2–8 pricing pages side by side at the same date |
| Which months/years have an archived copy |
Prompts: pricing_history_report (one company, the full story with dates), competitor_pricing (a market then vs now).
Dates can be 2021, 2021-06, 2021-06-15 or latest; the closest archived copy is used and its date is always shown.
Try these
"How did Slack's pricing change since 2016? Show every price increase in %."
"Compare the pricing of Notion, Coda and ClickUp today and in 2021."
"What did Figma charge for Professional in 2019?"
"Run pricing_history_report for linear.app/pricing."
Limits (set by the source)
Only pages the Wayback Machine archived. Most popular pricing pages have monthly copies going back years.
Pages that draw prices with JavaScript are empty in the archive; the server says so and you can try a nearby date.
Plan names are guesses from nearby headings; the context column and page text let the model check them.
archive.org is slow (10–30 s per page) and sometimes briefly offline; the server retries with backoff and caches everything it reads.
Part of the keyless MCP series
Open-source MCP servers that answer one market question each, with public data and no API keys.
Server | Question it answers |
What do users hate about competitor apps and games? (App Store + Steam reviews) | |
pricing-time-machine-mcp (this one) | How did a SaaS pricing page change over the years? (Wayback Machine) |
Which skills are tech companies hiring for, and which are rising? (HN Who is hiring) | |
What does each LLM cost, and did it get cheaper? (OpenRouter + price history) | |
What is a company about to launch? (certificate transparency logs) |
Development
uv sync --extra dev
uv run pytest # offline tests with a mocked Wayback Machine
uv run python scripts/smoke_live.py # live check against archive.org (1-3 min)
uv run --with rich python scripts/demo.py notion.so/pricing 2022-03 # terminal demo (vhs docs/demo.tape records the GIF)
npx @modelcontextprotocol/inspector uv run pricing-time-machine-mcp # click-through UIMIT © Ali Altunar
Available Tools
5 toolscompare_competitorsBRead-onlyIdempotent
Prices of 2-8 competitors' pricing pages side by side, as archived closest to the same date.
Inputs: urls (required), date, response_format. Returns: result
compare_pricingARead-onlyIdempotent
Compare one pricing page at two dates: prices and plans on each, plus what was added/removed.
Inputs: url (required), date_a (required), date_b, response_format. Returns: result
pricing_atARead-onlyIdempotent
Prices on a pricing page as archived closest to a date: each price with its plan guess, billing hints and context, plus the page text around the prices so you can read the plans.
Inputs: url (required), date, max_text_chars, response_format. Returns: result
pricing_snapshotsARead-onlyIdempotent
List the dates the Wayback Machine archived a page (one per month or year). Use it to see how far back history goes and to pick dates for pricing_at.
Inputs: url (required), per, to_year, from_year, +1 more. Returns: result
pricing_timelineARead-onlyIdempotent
How a pricing page's prices changed over the years. Reads points archived copies spread
across the range, groups identical price sets into periods and lists what was added/removed.
Inputs: url (required), points, to_year, from_year, +1 more. Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 5 tools
Each tool has a distinct query shape: listing archive dates, prices at one date, history over a range, two-date comparison, and multi-competitor comparison. There is mild overlap since pricing_at, pricing_timeline, and compare_pricing all return pricing data, but the descriptions make the boundaries (single vs. range vs. two-date vs. multi-page) clear enough to pick correctly.
Names split into a coherent pricing_* family (snapshots, at, timeline) for single-page temporal queries and a compare_* family for comparisons, which is readable and predictable. It is not a strict single verb_noun convention (pricing_at is noun_preposition), so it's slightly short of perfect.
Five tools is well-scoped for a niche Wayback pricing-history server, with each tool earning its place by covering a distinct query pattern. No redundant or filler tools.
The surface covers the full read-only lifecycle: discovering available dates, reading prices at a point, tracking a single page's history, comparing two dates of the same page, and comparing competitors at a common date. There are no obvious dead ends for the stated purpose.
Maintenance
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