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v0.2.0, foundational release

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@Craig-Horton Craig-Horton released this 05 May 16:27
· 134 commits to main since this release

v0.2.0, the deterministic pre-flight

aibvf-mcp ships its first feature-complete release. Six tools on stdio, an open protocol schema, deterministic four-pillar scoring with published benchmark ranges, and a working calibration loop in public.

What you can do with it

Register the server with any MCP-compatible client and ask your agent to score an AI initiative. The agent returns an Accelerate, Fix, or Stop classification with an EUR value range, decision confidence, applied module list, and a gap analysis. For Fix and Stop calls, a follow-up to recommend_improvements returns the specific pillar raises that flip the call toward Accelerate, each with a named action.

Tools shipped

  • score_initiative — Four-pillar score plus classification, EUR value range, decision confidence, applied modules, reasoning.
  • recommend_improvements — Pillar raise recommendations with named actions and projected new confidence.
  • calculate_pace_layer_drag — Annual Organisational Drag Cost in EUR from AI-tier vs operating-model misalignment.
  • validate_portfolio — Portfolio JSON validation against BVF v1.0 schema.
  • get_benchmark — Lookup of published benchmark rates by function and industry.
  • list_taxonomy — Valid enumerations for industries, functions, AI tiers, readiness levels.

Industry modules included

  • Healthcare clinical validation and regulatory overhead
  • Financial services capture multipliers
  • Cross-industry readiness capture rates from EY/Oxford
  • Prosci change-success calibration
  • Pace Layer drag calculation

Distribution

  • npm: npm install -g aibvf-mcp (package)
  • Python: pip install aibvf (package)
  • TypeScript engine: npm install @aibvf/core
  • MCP registry: live and searchable as aibvf

What is new vs 0.1.x

  • Anonymous telemetry, opt-out via AIBVF_TELEMETRY_DISABLE=1, point at your own backend with AIBVF_TELEMETRY_URL and AIBVF_TELEMETRY_KEY.
  • Pace Layer drag calculation as a standalone tool.
  • Benchmark corpus expanded to seven publishing sources.
  • CodeQL security scanning on every commit.
  • Stdio MCP server with deterministic, no-network scoring path.

What is next

  • Demo GIF for the README hero, recorded against Claude Desktop.
  • v0.3.0, additional industry modules and a CSV portfolio import path.
  • Public calibration cycle on the financial services benchmark ranges.

License

MIT for the schema, the scoring engine, and the MCP server. The benchmark corpus and certification marks are proprietary.

Author and maintainer

Craig Horton. Issues and PRs welcome, calibration debates expected.