MCP For Claude Marketplace
Accelerator Network Effects Engine

Accelerator Network Effects Engine MCP Connector for Claude

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Quantify the economic and relational value of accelerator ecosystems.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides specialized tools to model and quantify the network effects within accelerator ecosystems. Using Metcalfe's Law principles, it calculates network reach, collaboration value, and growth velocity. It accounts for geographic and sector clustering to provide accurate insights into how an ecosystem scales as participants increase. Use calculate_network_reach to find connection points, calculate_collaboration_value to estimate economic impact, and calculate_growth_velocity to measure expansion momentum.

acceleratornetwork-effectsecosystemeconomicsgrowth

3 tools expose this connector's capabilities to your AI agent.

calculate_growth_velocity

Determine how fast the ecosystem is expanding relative to its existing size

calculate_collaboration_value

Estimate the economic impact of interactions between different cohorts

calculate_network_reach

Calculate the total unique connection points available to a single cohort member

See how to talk to your AI agent using Accelerator Network Effects Engine.

How many unique connections can a cohort of 20 companies access if there are 150 alumni, 30 investors, and 10 partners?

The total network reach for this ecosystem is 210 unique connection points.

What is the estimated economic impact for a cohort of 15 companies with 100 alumni and a 15% cross-cohort collaboration rate, assuming an average deal size of $50,000?

The estimated collaboration value for this ecosystem is $75,000.

How fast is the ecosystem expanding with a cohort of 10, 50 alumni, and 5 investors?

The network is growing at a rate of 16.67% with a high expansion coefficient.

The `calculate_network_reach` tool calculates the total potential connection points by summing cohort members, alumni, investors, and partners, then adjusting for clustering intensity.

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