io.github.Bahamas1717/aibvf-mcp is an MCP server with 13 tools an agent can call, among them assemble_portfolio, assess_ai_initiative, calculate_pace_layer_drag. It answers at https://mcp.aibvf.com/api/mcp over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 6 of 6 times since 11 September 2026; the last check, on 19 October 2026, succeeded.
AI BVF: score AI portfolios Stop/Fix/Accelerate with decision confidence and pace-layer drag.
Description as the publisher wrote it.
| Tool | What it does |
|---|---|
assemble_portfolio | 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 Inputs: organization, initiatives, readiness |
assess_ai_initiative | 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 Inputs: proposal, industry, revenue_eur, function, ai_tier, readiness |
calculate_pace_layer_drag | 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 wai Inputs: revenue_eur, ai_tier, readiness, industry |
diagnose_process | 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 v Inputs: process_id, function, instances_per_year, fte_hours_per_instance, loaded_hourly_rate_eur, cycle_time_days |
get_benchmark | 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 driv Inputs: function, industry |
infer_readiness | 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 Inputs: function, handoffs, rework_rate, touch_ratio, automation_level, cycle_time_days |
list_taxonomy | 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, verd |
map_to_taxonomy | 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 Inputs: industry, function, ai_tier, readiness |
recommend_improvements | 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 Inputs: industry, revenue_eur, function, ai_tier, readiness, scores |
score_initiative | 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, c Inputs: industry, revenue_eur, function, ai_tier, readiness, scores |
score_portfolio | 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 i Inputs: portfolio, readiness |
sequence_portfolio | 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 Inputs: organization, initiatives, portfolio, readiness, constraints |
validate_portfolio | 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 st Inputs: portfolio |
Every block below points at https://mcp.aibvf.com/api/mcp. Pick your client and copy.
claude mcp add --transport http io-github-bahamas1717-aibvf-mcp https://mcp.aibvf.com/api/mcp
{
"mcpServers": {
"io-github-bahamas1717-aibvf-mcp": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://mcp.aibvf.com/api/mcp"]
}
}
}{
"mcpServers": {
"io-github-bahamas1717-aibvf-mcp": {
"url": "https://mcp.aibvf.com/api/mcp"
}
}
}{
"servers": {
"io-github-bahamas1717-aibvf-mcp": {
"type": "http",
"url": "https://mcp.aibvf.com/api/mcp"
}
}
}{
"context_servers": {
"io-github-bahamas1717-aibvf-mcp": {
"url": "https://mcp.aibvf.com/api/mcp"
}
}
}{
"mcpServers": {
"io-github-bahamas1717-aibvf-mcp": {
"serverUrl": "https://mcp.aibvf.com/api/mcp"
}
}
}{
"mcpServers": {
"io-github-bahamas1717-aibvf-mcp": {
"url": "https://mcp.aibvf.com/api/mcp"
}
}
}name: io.github.Bahamas1717/aibvf-mcp
version: 0.0.1
schema: v1
mcpServers:
- name: io.github.Bahamas1717/aibvf-mcp
type: streamable-http
url: https://mcp.aibvf.com/api/mcp{
"mcpServers": {
"io-github-bahamas1717-aibvf-mcp": {
"httpUrl": "https://mcp.aibvf.com/api/mcp"
}
}
}{
"mcpServers": {
"io-github-bahamas1717-aibvf-mcp": {
"type": "http",
"url": "https://mcp.aibvf.com/api/mcp"
}
}
}{
"mcpServers": {
"io-github-bahamas1717-aibvf-mcp": {
"url": "https://mcp.aibvf.com/api/mcp"
}
}
}goose://extension?url=https%3A%2F%2Fmcp.aibvf.com%2Fapi%2Fmcp&type=streamable_http&id=io-github-bahamas1717-aibvf-mcp&name=io.github.Bahamas1717/aibvf-mcp
It answered our last check on 19 October 2026 in 329 ms. Over 6 checks since 11 September 2026 it answered 6. Status here comes from Neuronto's own probes, not from the publisher.
13, as returned by the server's own tools/list on 12 September 2026: assemble_portfolio, assess_ai_initiative, calculate_pace_layer_drag, diagnose_process, get_benchmark, infer_readiness, list_taxonomy, map_to_taxonomy, and 5 more.
It answered our last check on 19 October 2026 in 329 ms. Over 6 checks since 11 September 2026 it answered 6.
Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://mcp.aibvf.com/api/mcp. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.
It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.
Publisher: io.github.bahamas1717. Endpoint host: mcp.aibvf.com. ARD identifier: urn:air:io.github.bahamas1717:mcp:aibvf-mcp.
First indexed 10 September 2026. The tools are exactly what the server returned; nothing on this page
is inferred from its name. Ranking in Neuronto search is never for sale.