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Signals
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Data productEstablishedMCP

MCP benchmark and evaluation index

Buyers comparing MCP options rely on anecdotes. A maintained benchmark with methodology becomes the citation standard — and a lead engine.

70Score

Opportunity score

70

confidence 75%

Related stars · 7d

+350.1k

4 tracked repos · est.

Trend runway

33mo

estimated demand lifespan

Avg breakout odds

65%

7-day cohort probability

Score anatomy

Every factor, its weight and its normalized value — the score is the weighted sum, nothing else.

Demand accelerationest.25%78
Ecosystem growthest.20%68
Commercial intentest.15%62
Solution gapest.15%68
Buyer capacityest.10%75
Trend longevityest.10%72
Implementation accessibility5%62
Demand78
Competition32
Monetization62
Complexity38

Demand trajectory — 90 days

+350.1k stars · 7d

Aggregate star velocity and momentum across the 4 repositories underlying this opportunity · estimated

Underlying repositories

The projects whose trajectories generate this opportunity.

Repositories underlying this opportunity
RepositoryScoreStars · 7dStage
paperclipai/paperclip101.3k stars · TypeScript79+5.5kSaturated
Panniantong/Agent-Reach96.8k stars · Python78+12.2kBreakout
Graphify-Labs/graphify126.1k stars · Python78+15.1kBreakout
morluto/rea191.5k stars · TypeScript77+317.3kSaturated

90-day execution plan

  1. Days 0–30

    Ship the wedge

    Build the smallest sellable slice of the data product and put it in front of teams already using paperclipai/paperclip.

  2. Days 30–60

    Prove willingness to pay

    Convert the MCP community's attention (demand 78/100) into 3–5 design partners at founding-customer pricing under a sponsorship motion.

  3. Days 60–90

    Systematize distribution

    Publish benchmark/comparison content targeting the topic's search demand and integrate into the ecosystems of the related repositories — the channel compounds while the trend has an estimated 33 months of runway.