AI BVF

{
  "id": "aix_4edc4f89bd",
  "name": "AI BVF",
  "operator": "(unclaimed - source: pulsemcp · publisher: github.com)",
  "description": "Scores AI investment portfolios as Stop, Fix, or Accelerate with decision confidence and pace-layer drag modeling.",
  "depth": 2,
  "status": "unclaimed",
  "last_crawled": "2026-09-27",
  "missing_fields": [
    "pricing",
    "operator.identity"
  ],
  "skills": [
    "github-ops",
    "media-catalog"
  ],
  "protocols": {
    "mcp": "https://mcp.aibvf.com/api/mcp",
    "a2a": null
  },
  "pricing": null,
  "regions": [
    "global"
  ],
  "languages": [
    "en"
  ],
  "reputation": {
    "tasks_completed": null,
    "dispute_rate": null,
    "p95_latency_ms": 1471,
    "uptime_30d": 1,
    "onchain_volume_30d_usd": null
  },
  "aix_score": 52,
  "verification": {
    "identity": "none",
    "health": "probe/24h",
    "pricing": "unknown",
    "last_check": "2026-09-27T11:00:52.512Z"
  },
  "pricing_model": "unknown",
  "links": [
    {
      "label": "homepage",
      "url": "https://www.pulsemcp.com/servers/bahamas1717-ai-bvf"
    },
    {
      "label": "repository",
      "url": "https://github.com/craig-horton/ai-bvf"
    },
    {
      "label": "listing",
      "url": "https://www.aibvf.com/protocol"
    }
  ],
  "avatar": "https://github.com/craig-horton.png?size=160",
  "socials": [
    {
      "label": "github",
      "url": "https://github.com/craig-horton"
    }
  ],
  "public_stats": {
    "npm_downloads": 6128
  },
  "profile": {
    "mcp_server": "io.github.Craig-Horton/aibvf-mcp",
    "mcp_version": "0.14.12",
    "tool_count": 13,
    "tools": [
      {
        "name": "assess_ai_initiative",
        "description": "The front door for one AI investment decision. CALL THIS FIRST when the user describes an AI idea in ordinary language or asks whether it should proceed. It resolves industry, revenue, business function, AI tier and organisational readiness, then returns one clarification covering every unresolved input or an Accelerate, Fix or Stop verdict. Ask that clarification once and call this tool again with the answers in the explicit fields. Use work_architecture to test whether the end-to-end workflow, affected roles, human decision rights and performance measures have been redesigned. A stated gap o"
      },
      {
        "name": "score_initiative",
        "description": "Canonical-field scorer for one AI initiative. CALL THIS when industry, revenue_eur, function, ai_tier and readiness are already known, or when re-scoring with measured pillar evidence. For a proposal written in ordinary business language, call assess_ai_initiative first; it resolves these fields and asks for anything missing. Pillar scores remain optional: missing pillars are estimated deterministically, reported through pillar_basis, and reduce decision confidence, while a fully estimated pass can never return Accelerate. Returns Accelerate, Fix or Stop, modelled gross and net EUR ranges, dec"
      },
      {
        "name": "score_portfolio",
        "description": "Score several AI initiatives as one AI BVF v1.0 portfolio and return the board-level position: counts of Accelerate / Fix / Stop, aggregate modelled EUR value range, mean decision confidence, the highest-value initiative, the highest-risk initiative, and every individual result. CALL THIS when the user has a portfolio document and needs to know what it contains before deciding funding or order, instead of looping score_initiative one initiative at a time. The single readiness value applies across every initiative: it changes capture rates and the pace-layer drag, so measure it with infer_readi"
      },
      {
        "name": "recommend_improvements",
        "description": "Turn a Fix or Stop verdict into the change plan that could earn a re-score, with pillar targets, named plays, owners, stop conditions, cost of waiting and a deadline. CALL THIS after score_initiative returns Fix or Stop, using the same five context fields and any scores or work-architecture evidence from that call. Do not use it to produce the initial verdict, sequence several initiatives or diagnose measured process waste; use score_initiative, sequence_portfolio or diagnose_process for those jobs. Do not call it for Accelerate unless a specific delivery risk needs testing before commitment. "
      },
      {
        "name": "calculate_pace_layer_drag",
        "description": "Quantify the annual EUR cost of an AI ambition outrunning the operating model: queues, hand-offs and slow decisions that prevent the organisation capturing the value already assumed in the case. CALL THIS when the user needs the cost of waiting for the organisation to change, or when a Fix plan needs a cost-of-waiting figure. Do not use it to score an AI initiative, estimate the implementation cost, or calculate a process saving: use score_initiative for the investment verdict, diagnose_process for a running process, and recommend_improvements for the change plan. revenue_eur sets the absolute"
      },
      {
        "name": "validate_portfolio",
        "description": "Check whether a supplied AI BVF v1.0 portfolio document has the shape the portfolio tools require, before scoring, sequencing, storing or sharing it. CALL THIS when the document came from a file, another system or hand-built JSON and its structure is uncertain. It checks required fields, taxonomy values and 0–100 pillar ranges only; it does not judge the evidence or calculate a verdict. Pillars may be bare numbers or { value, confidence } objects, both are valid. Use assemble_portfolio when the user has a list of initiatives in conversation and needs the document built for them, score_portfoli"
      },
      {
        "name": "get_benchmark",
        "description": "Look up the disclosed AI BVF planning rates behind the value model for one business function and industry. CALL THIS when the user wants to inspect the revenue-uplift and cost-takeout assumptions before scoring, or to compare the value drivers across functions. function selects the base rate range and named drivers; industry applies the multiplier, while universal returns the unadjusted base rate. External research in the evidence register frames the adoption and value problem but does not publish these function rates. The output is a rate, expressed as a fraction of revenue, not an initiative"
      },
      {
        "name": "list_taxonomy",
        "description": "Return the exact industry, function, AI-tier and readiness values every AI BVF calculation accepts. CALL THIS when the caller needs the complete allowed list or when a free-text value is not obvious. It returns taxonomy only, no score, verdict or language mapping. Use map_to_taxonomy when the user has said customer service, banking, RPA or bureaucratic and you need the one canonical value; use this tool when they need the whole menu of values to choose from. Takes no parameters. Pure deterministic lookup — no network, auth, or side effects."
      },
      {
        "name": "diagnose_process",
        "description": "Diagnose a single existing business process from operational evidence and return the intervention, modelled net EUR saving, efficiency gain, verdict and confidence. CALL THIS when the user can describe a process already running, including volume, touch time, waiting, hand-offs, rework, automation and cost. instances_per_year × fte_hours_per_instance × loaded_hourly_rate_eur builds the labour baseline, direct_spend_eur adds the non-labour baseline, and readiness caps the saving that the organisation can realise. The friction signals select the intervention: low automation points to Automate, ma"
      },
      {
        "name": "infer_readiness",
        "description": "Measure organisational readiness from process data, so the investment case does not depend on an untested maturity claim. CALL THIS before score_initiative, score_portfolio or calculate_pace_layer_drag when the user can provide at least two of five signals: hand-offs, rework, touch ratio, automation level and cycle time. function selects the comparison medians for hand-offs and cycle time; more signals increase confidence and disagreement between them reduces it. claimed_readiness is optional, but pass it when the organisation has declared itself agile, traditional or siloed, because the retur"
      },
      {
        "name": "sequence_portfolio",
        "description": "Turn a scored AI portfolio into three waves with gates over a configurable horizon, so the roadmap respects the change capacity of each business function. CALL THIS after score_portfolio when the user asks what to stop, fund first, defer or fit into the next 90 days. It does not change any verdict or re-score the business case. Stops enter wave 1 to reclaim budget and attention, quicker Accelerates enter wave 2, complex Accelerates and Fixes enter wave 3 behind their re-score gates. Pass the portfolio returned by score_portfolio directly through portfolio, or pass organization plus initiatives"
      },
      {
        "name": "map_to_taxonomy",
        "description": "Map everyday business language to the canonical AI BVF values required by the scoring tools. CALL THIS when the user says customer service, procurement, banking, GenAI copilot or bureaucratic and the matching enum is not certain. Pass only the fields written in free text; each returns the canonical value, what it matched on, or null with suggestions. A null result requires the user to choose from the suggestions, because a plausible guess would change the score. Use list_taxonomy when the user needs every permitted value, then pass the mapped values into score_initiative, diagnose_process, get"
      },
      {
        "name": "assemble_portfolio",
        "description": "Assemble a valid AI BVF v1.0 portfolio document from loose inputs, deterministically. Agents arrive with initiative names, plain-language functions and half the pillar scores, then hand-build the portfolio JSON and get the shape wrong; this tool builds it right. Give it the organisation (name plus industry in canonical or everyday language) and one entry per initiative (name, function, ai_tier, plus whatever pillar scores you actually have as bare numbers) and it returns the finished document: aliases resolved through the same mapping as map_to_taxonomy, ids generated from names and deduplicat"
      }
    ],
    "profiled_at": "2026-09-27T11:00:52.512Z"
  },
  "unreachable": false,
  "payment_method": "open"
}