nova.mcp-bcp-counting

nova.mcp-bcp-counting

Enables Claude to guide developers through structured complexity estimation using BCP Plus methodology, counting 13 dimensions and persisting results for H/BCP tracking.

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nova.mcp-bcp-counting

MCP Server for BCP Plus complexity counting — 10 functional + 3 non-functional dimensions.

Built on the BCP Plus methodology (CI&T, May 2026). Enables Claude to guide developers through structured complexity estimation during planning or coding sessions in VSCode, Claude Code, and Cursor.


What it does

When a developer asks Claude to count BCP for a story, Claude automatically:

  1. Assesses story maturity — warns if the story is too vague to count reliably
  2. Counts each dimension in isolation — 1 prompt per dimension, reducing cross-dimensional interference (per whitepaper recommendations)
  3. Calculates BCP Plus total — Functional BCP + NFR BCP + NFR Ratio + risk classification
  4. Persists the result — saves to .bcp/counts.json in the project for H/BCP tracking

Quick start

Prerequisites

  • Node.js ≥ 18
  • One of: VSCode, Claude Code, or Cursor

Install

# Clone and build
git clone https://github.com/danielvm-git/nova.mcp-bcp-counting.git
cd nova.mcp-bcp-counting
npm install
npm run build

# Install for your platform
node dist/installer/install.js --platform vscode       # VSCode
node dist/installer/install.js --platform claude-code  # Claude Code
node dist/installer/install.js --platform cursor       # Cursor

# Or interactive (asks which platform)
node dist/installer/install.js

Use

Open a story file or paste it in the chat, then ask Claude:

Count the BCP Plus for this story.
Decompose this epic into stories and estimate the BCP for each.
Show me the project BCP metrics so far.

The 13 dimensions

Functional (D01–D10) — inherited from BCP open-source release

# Dimension CV% Stability
D01 Business Rules 19.2% Moderate
D02 Interface Elements 40.1% High ⚠️
D03 Roles / Permissions 33.2% High ⚠️
D04 Solution Variabilities 47.1% Critical 🔴
D05 Boundaries 44.6% Critical 🔴
D06 Domain Entities 38.6% High ⚠️
D07 New Domain Entities 24.8% Moderate
D08 Background Processes 21.4% Moderate
D09 Notifications 13.5% Stable ✅
D10 Audits 13.2% Stable ✅

Non-functional (D11–D13) — BCP Plus exclusive

# Dimension CV% Stability
D11 Quality Attributes 22.5% Moderate
D12 Security & Compliance 10.5% Stable ✅
D13 UX & Accessibility 9.8% Most stable

CV% = coefficient of variation from the 43-story empirical baseline (CI&T Flow team, April 2026).
D04 and D05 are flagged as LOW CONFIDENCE in all outputs — always validate with the team.

Fibonacci scale

Label Score
XS 1
S 2
M 3
L 5
XL 8

NFR Ratio risk levels

NFR Ratio Risk Action
0–15% Primarily functional Standard delivery
15–30% Balanced Monitor NFR during sprint
30–50% NFR-heavy 🟡 Architectural spike recommended
>50% Extreme 🔴 Architectural review required

Available MCP tools

Tool Description
assess_story_maturity Score story maturity 1–5 and get expected CV%
list_dimensions List all 13 dimensions with stability status
get_dimension_guide Full sizing criteria + per-dimension prompt for a given D-id
count_dimension Get counting context for a dimension (used by Claude per-dimension)
calculate_bcp_plus Aggregate scores → Functional + NFR + NFR Ratio + risk
decompose_epic Get guidance to split an epic into well-sized stories
save_story_count Persist a count to .bcp/counts.json
get_project_metrics Read all saved counts and project totals

Story maturity and counting reliability

Story maturity is the strongest predictor of counting accuracy:

Maturity Expected CV Recommendation
< 3 ~39.5% ⚠️ Do not count — refine first
= 3 ~15.5% Acceptable — flag open items
> 3 ~12.2% ✅ Ready to count

A story reaches maturity 3+ when it has:

  • A defined actor
  • Clear acceptance criteria (Given/When/Then)
  • Business value stated
  • Key entities named

Project metrics

After counting stories, BCP data is saved locally in .bcp/counts.json:

{
  "project": "my-project",
  "summary": {
    "story_count": 12,
    "total_bcp": 148,
    "avg_bcp_per_story": 12.3,
    "avg_nfr_ratio_pct": 18.5
  },
  "stories": [...]
}

Use total_bcp + actual delivery hours to compute H/BCP (hours per BCP point) — the key productivity indicator for AI-augmented teams.


Platform config files generated

Platform File
VSCode .vscode/mcp.json
Claude Code via claude mcp add
Cursor .cursor/mcp.json

References


License

MIT — © CI&T

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