Recall
Recall's pricing URL resolves, but plan structure is not surfaced clearly enough for an agent to enumerate without hand-parsing. No per-unit price was found on the page; an agent has no direct way to estimate the cost of a single task. Public API documentation is reachable without an auth wall.
Recall pricing
We’re still verifying Recall’s pricing
Pricing details are not publicly disclosed beyond a free tier; no monetary amounts appear on the page, so pricing model is marked unverified and most numeric fields are null.
Source of truth: www.recall.wiki/
How Recall scores on the agent-ready dimensions
Public pricing
10 / 15
Usage-based / metered
0 / 25
Self-serve checkout
0 / 15
Public API
15 / 15
Low / no minimum
0 / 10
Unauth automated payment
0 / 10
Bonus (machine-readable pricing)On top of /100 base
0 / 5
Total
27 / 100
Six-step check: can an agent actually buy from Recall?
Discover price
Select a plan
Pay per task
Avoid a sales call
API docs without auth
Estimate cost upfront
Pros and cons for AI agents
Observational summary written by xpay from the signals captured on 2026-05-06. Not a review of the product — only of its current pricing posture for agent buyers.- Pricing is publicly visible on an indexable page — agents can read tiers without scraping past auth.
- No per-unit price was advertised, so an agent has no way to estimate the cost of a single task.
- All advertised tiers route to a sales contact form; an agent cannot complete a purchase autonomously.
- API documentation is gated or absent; an agent cannot inspect the integration surface without authentication.
- No /.well-known/ai-pricing.json or equivalent machine-readable pricing manifest is published — agents must rely on HTML scraping.
How Recall could lift its score
Add a per-unit price (e.g. $X / 1K calls) to the pricing page so an agent can compute its own cost before committing.
| pricing_visible | true |
| headline_phrasing | Your knowledge is your edge — Save what matters. Write what you think.Curate an AI that knows what you know. |
| tier_count | 1 |
| lowest_paid_entry_usd | null |
| free_tier | false |
| free_tier_terms | null |
| per_unit_price | null |
| annual_required | false |
| self_serve_paid_tiers | 0 |
| sales_only_tiers | 0 |
| public_api_docs_url | https://docs.recall.it/ |
| api_docs_auth_walled | false |
| ai_pricing_json_present | false |
| agents_txt_present | false |
| anonymous_purchase_path | false |
| per_unit_classification | null |
| usage_headline_present | false |
| custom_tier_present | false |
| agent_friendly | {"ai_pricing_json":false,"agents_txt":false,"llms_txt":false,"sitemap_xml":true,"mcp_server_card":false,"agent_skills_index":false,"x402_supported":false} |
View raw extracted page text →
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See agent-ready picksRecall
27
/ 100 (rubric v1.1)Note Taking
Your knowledge is your edge — Save what matters. Write what you think.Curate an AI that knows what you know.
1
No
Sales-led
0 / 0
Public
No
Not published
2026-05-06
Discovery files and protocols
Side-channel signals — informational, not part of the score. Each protocol is independent; adoption signals the publisher is thinking about agent buyers.ai-pricing.json
agents.txt
llms.txt
sitemap.xml
MCP Server Card
Agent Skills
x402 / MPP
Compare Recall with peers
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64
Chamu
60
Waspnote
60
Spellar AI
60
DoneNote
59
Instaminutes
58
Standard Notes
56
Collato
56
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