MCP For Claude Marketplace
AI R&D Efficiency Analytics

AI R&D Efficiency Analytics MCP Connector for Claude

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Evaluate AI R&D productivity by correlating spend with innovation outputs.

4 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

This MCP server provides a specialized analytics engine to measure the return on investment of Artificial Intelligence research. By correlating financial R&D spend with tangible outputs like model releases and patent filings, it calculates a normalized R&D efficiency score. Users can use calculate_efficiency_score to determine productivity, compare_to_benchmarks to see how they stack up against industry standards, analyze_innovation_composition to balance IP versus product velocity, and get_efficiency_trends to track momentum over time.

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

analyze_innovation_composition

Breaks down whether efficiency is being driven by intellectual property (patents) or product velocity (releases)

calculate_efficiency_score

Calculates the core R&D efficiency metric for a specific period or project

compare_to_benchmarks

Compares a specific entity's efficiency against established industry standards

get_efficiency_trends

Evaluates how efficiency is changing over multiple periods

See how to talk to your AI agent using AI R&D Efficiency Analytics.

Calculate my R&D efficiency. I spent 500000 Euros, released 5 models, filed 2 patents, and my time to market was 8 months.

Your R&D efficiency score is 72. Your productivity status is Optimal, with improvement opportunities in increasing patent filings to balance your product velocity.

Compare an efficiency score of 65 against an industry intensity of 0.15.

Your score is 5 points below the industry average. You are currently in the Average performance tier.

Analyze my innovation composition for 10 model releases and 2 patent filings with a 1000000 Euro spend.

Your innovation is Product-heavy, with a release ratio of 83% and a patent ratio of 17%.

It is a normalized metric from 0 to 100 that measures how effectively capital is converted into innovation, such as through `calculate_efficiency_score`.

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