What is the RICE framework?

RICE is a prioritization method that uses Reach, Impact, Confidence, and Effort to score features. This MCP automates those calculations for you.

Can I account for technical dependencies?

Yes. You can use the roadmap recommendation capability to create a plan that respects the order in which features must be built.

How do I prioritize features that align with my strategy?

You can provide an alignment weight when generating a ranked list to boost the scores of strategic features.

Which AI clients can I use with this MCP?

You can use this MCP with any compatible client, including Claude, Cursor, Windsurf, and VS Code.

Can I find easy wins in my backlog?

Yes. Use the search capability to filter for features that meet specific low-effort or high-impact criteria.

How is the RICE score calculated?

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

Can I account for feature dependencies in the roadmap?

Yes, when using get_roadmap_recommendation, you can set the dependency flag to ensure prerequisites are scheduled before the features that depend on them.

How do I boost features that align with my business goals?

You can use the alignmentWeight parameter in get_feature_prioritization to apply a multiplier to features that have high strategic relevance.

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Connect Startup Feature Prioritization to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Turn messy feature lists into ranked, actionable product roadmaps.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 4 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through Startup Feature Prioritization.

01
Calculate rice score
This capability calculates a single RICE score for a specific feature based on your provided metrics.
02
Get feature prioritization
This capability generates a ranked list of features using RICE scores and optional strategic alignment weights.
03
Get roadmap recommendation
This capability builds a sequential execution plan that respects feature dependencies and priority levels.
04
Search features by metric
This capability filters your feature list to find specific items based on cost or performance criteria.

Real work

What teams actually run

Backlog Grooming

Use the RICE scoring capability to clean up a messy list of ideas and find the real winners.

Roadmap Planning

Generate a sequential execution plan that ensures prerequisites are built before dependent features.

Strategic Pivot

Apply alignment weights to re-rank the entire backlog toward a new company objective.

Resource Allocation

Filter for low-effort features to find quick wins for a small engineering team.

One connector, every AI

Startup Feature Prioritization works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

Building your own app? The connector is yours to use.

You don't need a client to put Startup Feature Prioritization to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

906ms average. Fast in production.

Startup Feature Prioritization is checked daily against the live service.

Daily averagePeak 1132ms

Oct 3Today

Fastest day: 784ms
Slowest day: 1132ms
14-day trend: Stable+1%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 4 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Startup Feature Prioritization, so you can see the experience inside your AI.

It does not authenticate your account with Startup Feature Prioritization. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Startup Feature Prioritization Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_4ocNOWMRq6J8tK9XifIxwhMJeXY1Ak2UKkofbRWA/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — Startup Feature Prioritization capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "startup-feature-prioritization-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_4ocNOWMRq6J8tK9XifIxwhMJeXY1Ak2UKkofbRWA/mcp"
    }
  }
}

Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Startup Feature Prioritization in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Startup Feature Prioritization owners hand off.

Product leaders who need to move from intuition to data-driven decision making.

01
Product Managers
They hand off feature lists to the AI to generate prioritized backlogs.
02
Product Owners
They use the capability to build sequential execution plans for development teams.
03
Startup Founders
They use it to ensure engineering effort is spent on the highest-impact features.

FAQ

Questions Startup Feature Prioritization owners ask.

01
What is the RICE framework?
RICE is a prioritization method that uses Reach, Impact, Confidence, and Effort to score features. This MCP automates those calculations for you.
02
Can I account for technical dependencies?
Yes. You can use the roadmap recommendation capability to create a plan that respects the order in which features must be built.
03
How do I prioritize features that align with my strategy?
You can provide an alignment weight when generating a ranked list to boost the scores of strategic features.
04
Which AI clients can I use with this MCP?
You can use this MCP with any compatible client, including Claude, Cursor, Windsurf, and VS Code.
05
Can I find easy wins in my backlog?
Yes. Use the search capability to filter for features that meet specific low-effort or high-impact criteria.
06
How is the RICE score calculated?
The score is calculated by multiplying Reach, Impact, and Confidence, then dividing the result by Effort.
07
Can I account for feature dependencies in the roadmap?
Yes, when using get_roadmap_recommendation, you can set the dependency flag to ensure prerequisites are scheduled before the features that depend on them.
08
How do I boost features that align with my business goals?
You can use the alignmentWeight parameter in get_feature_prioritization to apply a multiplier to features that have high strategic relevance.

Explore

More in Product Management

Connect Startup Feature Prioritization to Claude, Cursor, ChatGPT & more

Your AI does the work. We keep it safe and sound.

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-04

Calculate rice score

Get feature prioritization

Get roadmap recommendation

Search features by metric

What teams actually run

Backlog Grooming

Roadmap Planning

Strategic Pivot

Resource Allocation

Building your own app? The connector is yours to use.

Startup Feature Prioritization Connector

Claude Desktop

Product Managers

Product Owners

Startup Founders

What is the RICE framework?

Can I account for technical dependencies?

How do I prioritize features that align with my strategy?

Which AI clients can I use with this MCP?

Can I find easy wins in my backlog?

How is the RICE score calculated?

Can I account for feature dependencies in the roadmap?

How do I boost features that align with my business goals?

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