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Accelerator Peer Learning Value Engine

Accelerator Peer Learning Value Engine MCP Connector for Claude

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Quantify the economic and structural value of startup accelerator networks.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides specialized calculation engines to measure the impact of peer-to-peer learning within startup cohorts. It allows AI agents to quantify network health and economic utility through three core capabilities: calculate_peer_learning_metrics for assessing connectivity and density, estimate_collaboration_value for translating interactions into monetary impact, and analyze_knowledge_flow to evaluate how structured events drive network intelligence. By accounting for company stages and sector overlap, it transforms raw connection data into actionable organizational intelligence.

acceleratorstartupnetwork-analysiseconomicspeer-learning

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

analyze_knowledge_flow

Evaluates how structured events are contributing to the overall network intelligence

calculate_peer_learning_metrics

Provides a snapshot of the current network's health and connectivity

estimate_collaboration_value

Translates network activity into a monetary value representing the economic utility of the cohort

See how to talk to your AI agent using Accelerator Peer Learning Value Engine.

Calculate the network density and peer learning score for a cohort with these connections: [{"companyA": "StartupA", "companyB": "StartupB"}] and a sector overlap of 0.8.

The cohort has a peer learning score of 0.85 and a network density of 0.42.

What is the estimated collaboration value for two collaborations worth 5000 each, with an outcome correlation of 1.2 and stage weights of {"Early Stage": 1.5}?

The total estimated collaboration value is 18000.0.

Analyze the impact of a recent workshop on the network connections: [{"newConnections": [{"companyA": "A", "companyB": "B"}]}] and existing connections: [{"companyA": "C", "companyB": "D"}].

The workshop resulted in an event impact score of 0.75 and increased the connection catalyst rate significantly.

The engine uses `estimate_collaboration_value` to sum the worth of individual collaborations, adjusting them by an outcome correlation factor and specific weights assigned to different company stages.

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