MCP For Claude Marketplace
Startup Feature Prioritization

Startup Feature Prioritization MCP Connector for Claude

A+

Prioritize product features using the RICE framework.

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

This MCP server provides tools to quantify and rank product features using the RICE (Reach, Impact, Confidence, Effort) framework. It allows product managers to calculate individual scores with calculate_rice_score, generate ranked lists via get_feature_prioritization, and build execution plans with get_roadmap_recommendation. You can also filter features using search_features_by_metric to find high-impact or low-effort opportunities.

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

calculate_rice_score

Calculates the individual RICE score for a specific feature

get_feature_prioritization

You can optionally provide an alignment weight to boost strategic features. Generates a ranked list of features based on their RICE scores and strategic alignment

get_roadmap_recommendation

Optionally include dependencies to ensure prerequisites are scheduled first. Provides a sequential execution plan that respects dependencies and priority

search_features_by_metric

Filters and retrieves features based on specific performance or cost criteria

See how to talk to your AI agent using Startup Feature Prioritization.

Calculate the RICE score for a feature with 500 reach, 3 impact, 0.8 confidence, and 2 months of effort.

The RICE score for this feature is 600.

Show me a ranked list of all features.

1. Feature A (Score: 1200) 2. Feature B (Score: 850) 3. Feature C (Score: 400)

Find features that require less than 3 person-months of effort.

The following features meet your criteria: Feature B and Feature D.

The score is calculated by multiplying Reach, Impact, and Confidence, then dividing the result by Effort.

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