Seolup — Low-Competition Keywords, Scored by Real SERP Weakness

One engine, two surfaces

From a seed keyword to a page that ranks.

The same engine answers on the web and to an AI agent over MCP, drawing from the same credit balance.

analysis.run run_id · lf_a7c3f0e1 Example run

09:45:02
seed 'best soil mix for raised garden beds' web
09:45:03
Labs: +48 keywords
09:46:11
SERP fetch · cache hit 12/48
09:47:40
signals: 2× forum, AI Overview cites 2 UGC domains
09:47:55

'best crm software' → score 11 · fortress → discarded the engine also tells you when NOT to attack
09:47:58
score 72 · easy_win
09:48:03
sent to Claude Code via MCP · run_id MCP Claude CodeCursor

serp · 'best soil mix for raised garden beds' example serp

reddit.com › r/gardening forum
Best soil mix? Sharing what worked for me
AI Overview · cites 2 UGC domains
quora.com forum
What soil ratio for a new raised bed?
→ your page ranks here easy_win

weak SERP: 2 forums + AI Overview above the fold

The problem

Keyword difficulty is a guess.

Most tools spit out a KD number and call it a day — ignoring beatable forums, thin pages, AI Overviews, ads. You chase keywords that look easy and aren't.

Fake scores.
Real signals ignored.
Rankings that never show up.

Keyword how to fix a wobbly ceiling fan

KD 18 looks easy

vs

Vulnerability 22 trap

Soft targets 45% → 50%

0

Content weakness 25% → 27.8%

0

SERP visual 20% → 22.2%

100

No AI Overview → GEO/AEO excluded, weights renormalized over 3 groups (0.45 + 0.25 + 0.20 = 0.90):
0 × 0.5 + 0 × 0.278 + 100 × 0.222 = 22.2 → 22

very_low Looks easy by KD — it's actually a fortress of strong top-10 pages.

The vulnerability engine

A 0–100 score you can audit.

Each keyword gets a weighted score across four signal groups — beatable sources, content weakness, SERP layout, and AI Overview citation opportunity. You see the why, never a black box.

"best soil mix for raised garden beds" KD 24

Soft targets 45% → 30.6

68

2 forum threads (rank 1, 3) + 1 directory (rank 7) → raw 20.4 → round(20.4 × 100 / 30) = 68 score.ts:53–63

Content weakness 25% → 20.5

82

3 thin pages < 500w (2 in top-3 at +30, 1 in top4–10 at +12) + title without keyword +6 + missing H1 +4 → 82 score.ts:77–101

SERP visual 20% → 11.0

55

within SERP visual base 100 − 45 · AI Overview = 55 no ads · no local pack · first organic above the fold — score.ts:110–126

GEO / AEO 10% → 10.0

100

the same AI Overview cites 2 UGC domains (Reddit + the forum) → ugcRefs ≥ 2 → 100 score.ts:136–148

30.6 + 20.5 + 11.0 + 10.0 = 72.1 score.ts:217–225

72 72.1 → 72

high · 70–84 easy_win KD 24 < 30 + score ≥ 70 → easy_win

The catalog

The sources and soft targets we detect.

Not 35 separate algorithms — one domain-matching mechanism across four weighted categories, plus content and layout signals.

UGC / FORUMS ×1.0

SOCIAL ×0.9

DIRECTORY ×0.8

THIN AGGREGATORS ×0.7

Content & layout signals — no domain weight

Thin page (< 500 words)Keyword absent in <title>No <h1>AI Overview presentAds above first organicLocal PackFirst organic below the foldAI Overview cites UGC

Your first analysis is on us. Start free

Prioritization

Know what to attack at a glance.

Example data easy_win hidden_gem trap fortress

raised bed soil KD 24 · 72 wobbly ceiling fan KD 18 · 22 vegan protein KD 21 · 88 niche edm KD 54 · 78 best crm KD 89 · 11

easy_win

Low KD + high vulnerability — go now.

hidden_gem

High KD, but the SERP is actually weak.

trap

Looks easy, isn’t.

fortress

Skip it.

Fewer pieces, more rankings

Attack a topic, not a keyword.

We group keywords that share the same top-10 URLs (Jaccard overlap ≥ 0.3 by default). One cluster = one piece of content that captures the whole group, with aggregated volume.

cluster.ts · jaccard() · threshold 0.3

clusters Example run

best soil mix for raised garden beds 4 kw 8,180/mo score 72

best soil mix for raised garden beds 3,600/mo cluster key
raised bed soil mix 2,400/mo 62% overlap
soil for raised vegetable beds 1,300/mo 45% overlap
what soil for raised garden bed 880/mo 38% overlap

Shared top-10 URLs

how to build a raised garden bed 4 kw 10,620/mo score 64

how to build a raised garden bed 5,400/mo cluster key
diy raised garden bed plans 2,900/mo 55% overlap
cheap raised bed ideas 1,600/mo 41% overlap
raised bed height for vegetables 720/mo 33% overlap

Shared top-10 URLs

what to plant in raised beds 3 kw 6,100/mo score 58

what to plant in raised beds 3,100/mo cluster key
raised bed vegetable garden layout 1,900/mo 47% overlap
companion plants for raised beds 1,100/mo 36% overlap

Shared top-10 URLs

In the product

The full table, exportable.

Every analysis gives you the complete table — score, label, quadrant, cluster, volume, KD — with live polling while it runs. Download it as CSV and work it anywhere.

app.seolup.io/dashboard/runs Example data

Credit balance 100 Free plan · early access

Recent analyses

raised garden beds 48 kw
vegan protein blends 32 kw
standing desk deals 12 / 40

Scoring 47 / 48 keywords · 47 credits

Keyword	Volume	KD	Score	Band	Quadrant	Cluster
vegan protein for runners	1,300	21	88	Very high	easy_win	vegan protein
niche edm subgenres explained	590	44	76	High	hidden_gem	edm subgenres
best soil mix for raised garden beds	2,400	24	72	High	easy_win	raised garden beds
cheap standing desk under $200	1,900	26	63	Medium	trap	standing desks
best budget mirrorless camera	8,100	57	34	Low	fortress	mirrorless cameras
how to fix a wobbly ceiling fan	3,600	18	22	Very low	trap	ceiling fan repair
how to descale a keurig	2,900	20	scoring…	—	—	keurig maintenance

Showing 7 of 48 keywords · Example data

Your first analysis is on us.

Get early access

For AI agents 6 MCP tools

Your agent researches keywords without leaving the chat.

Claude Desktop and Claude Code call the engine in plain language, with the same gates and the same balance as the web. No exporting, no copy-paste.

seolup · MCP over stdio Example

you find easy keywords around "raised garden beds"

agent find_low_competition_keywords({ seed: "raised garden beds", location: "United States" })

→ run_id run_a1b2c3 · 48 keywords · 1 credit each

agent get_analysis_results({ run_id: "run_a1b2c3" })

keyword	score	quadrant
best soil mix for raised garden beds	72	easy_win
raised garden bed drainage layer	71	easy_win
diy raised bed on concrete patio	70	hidden_gem

agent Ranked 48 keywords. Top pick scores 72 (easy_win). 32 credits left.

claude_desktop_config.json

{
  "mcpServers": {
    "seolup": {
      "command": ".../mcp/.bin/tsx",
      "args": [".../mcp/index.ts"],
      "env": {
        "INSFORGE_URL": "https://….insforge.app",
        "INSFORGE_ANON_KEY": "eyJ…",
        "SEOLUP_EMAIL": "you@email.com",
        "SEOLUP_PASSWORD": "…"
      }
    }
  }
}

find_low_competition_keywords mcp/tools.ts:425 spends credits

get_analysis_results mcp/tools.ts:585

list_analysis_runs mcp/tools.ts:649

analyze_serp_weakness mcp/tools.ts:694

cluster_keywords mcp/tools.ts:780

get_credit_balance mcp/tools.ts:849

Works with any MCP client Claude Desktop Claude Code Cursor Windsurf

A shared balance

The same credits on web and MCP.

1 credit per keyword analyzed, atomic and shared. A pre-gate rejects the spend BEFORE touching DataForSEO if there's no balance, with a daily cap and a concurrent-run limit.

lowfruits_check_spend_allowance pre-gate lowfruits_spend_credits atomic debit effectiveTier shared web + MCP

0–100 Engine score scale

1 credit = 1 keyword Atomic, shared spend

37–85 Observed score range · prod smoke Jul 2026

credit_ledger Example data

timestamp	keyword	kind	delta	balance_after
Jul 05 · 09:48:12	raised garden beds	analysis_spend	-48	32
Jul 05 · 09:31:40	wobbly ceiling fan	analysis_spend	-12	80
Jul 05 · 09:05:22	raised bed drainage	analysis_spend	-8	92

Daily cap 68 / 200 credits today

In progress

What's coming next.

Roadmap

Local/EMD mode

Striker Score, service×city geo-permutation, EMD domain availability.

Roadmap

Remote MCP (HTTP + OAuth)

Connect by pasting a URL, no terminal.

Roadmap

In-app connection guide

/dashboard/ai/mcp

Roadmap

get_content_brief

With On-Page data.

Pricing

Simple pricing, early access.

Free

€0

100 welcome credits

100 welcome credits
Up to 5 analyses / day
SERP vulnerability score
No card required

Start free

Early access pricing

Starter

€19 /mo

2,000 credits / month

2,000 credits / month
Unlimited analyses
Full analysis history
Email support

Start with Starter

Early access pricing

Pro

€49 /mo

10,000 credits / month

10,000 credits / month
Unlimited analyses
Full analysis history
Priority support

Go Pro

Your first analysis is on us.

The cheapest entry plan among SERP-analysis keyword tools — verified July 2026.

FAQ

Questions, answered

What is SERP vulnerability?

A 0–100 score measuring how beatable the current search results are, based on real signals like forums, thin pages, and AI Overviews.

How is it different from keyword difficulty?

KD is a guess. Vulnerability analyzes actual SERP makeup: UGC, layout, AI Overview citations. It shows real opportunity, not a made-up number.

What signals do you analyze?

Beatable forum results (Reddit, Quora), thin pages, AI Overview and its sources, ads pushing organics down, and local pack presence.

What are the 4 quadrants?

easy_win: high vulnerability, low KD. hidden_gem: high vulnerability, high KD. trap: low vulnerability, low KD. fortress: low vulnerability, high KD.

What is MCP, and why does it matter?

MCP (Model Context Protocol) is an open standard that lets AI assistants call external tools directly, instead of you copy-pasting data between apps. For keyword research, it means Claude Desktop or Claude Code can query Seolup, get real SERP data back, and keep working — no browser tab required.

What does MCP-native mean?

Claude Desktop and Claude Code can directly call Seolup’s research tools via MCP, using shared credits with the web app.

How does credit sharing work?

Credits are pooled. Use them in the web app or via MCP. One balance, no separate limits.

Is there a free plan?

Yes, 100 welcome credits and 5 analyses/day. No credit card required. Full access to all features.

Seolup is a keyword research engine built around real SERP vulnerability. It scores every keyword 0-100 by reading signals other tools ignore — beatable forums, AI Overviews, layout — sorts it into 4 quadrants, groups it by intent, and exports everything. The same research is available on the web and to AI agents over MCP, sharing one credit balance.

Start finding easy wins.

Get early access — 100 free credits, no card

Connect the MCP Seolup for AI agents

Easy keywords are real. We find the actual ones.

From a seed keyword to a page that ranks.

Keyword difficulty is a guess.

A 0–100 score you can audit.

The sources and soft targets we detect.

Know what to attack at a glance.

Attack a topic, not a keyword.

The full table, exportable.

Your agent researches keywords without leaving the chat.

The same credits on web and MCP.

What's coming next.

Local/EMD mode

Remote MCP (HTTP + OAuth)

In-app connection guide

get_content_brief

Simple pricing, early access.

Free

Starter

Pro

Questions, answered

Start finding easy wins.