Aibvf MCP vs Cpm Planner
A side-by-side look at the Aibvf MCP and Cpm Planner MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Aibvf MCP for product management work as a local process; choose Cpm Planner for product management as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Aibvf MCP when
- You need dedicated capabilities in the Product Management domain.
- You prefer a local stdio subprocess transport.
- You want tools like
assess_ai_initiative, score_initiative, score_portfolio.
Choose Cpm Planner when
- You need dedicated capabilities in the Product Management domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You have the keys it needs:
CPM_PLANNER_DB. - You want tools like
plan.release.compile, plan.release.diff, plan.submit.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Product Management | Product Management |
| Quality signal | 61/100 · Good | 63/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | No auth required |
| Pricing | Not declared | Free |
| Required env vars | None listed | CPM_PLANNER_DB |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 0 |
| Directory activity | 1 views 0 installs 0 upvotes | 0 views 0 installs 0 upvotes |
| Tools | 13 | 25 |
| Full listing | View Aibvf MCP | View Cpm Planner |
Tools & capabilities
Aibvf MCP tools 13
assess_ai_initiativeThe 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 or missing work architecture evidence blocks Accelerate and stays visible in the audit trail. Pillar scores and work architecture evidence remain optional inputs, but unresolved values are never guessed and cannot unlock Accelerate. Use score_initiative when the canonical fields are already known, score_portfolio for several initiatives, and diagnose_process for measured waste in a running process. Deterministic calculation with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.score_initiativeCanonical-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 score, while a fully estimated pass can never return Accelerate. Returns Accelerate, Fix or Stop, modelled gross and readiness-adjusted EUR benefit ranges, decision score, sensitivity, assumptions and an audit trail. Use score_portfolio for several initiatives and diagnose_process for measured waste in an existing process. Deterministic calculation with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.score_portfolioScore 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 score, 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_readiness first when process data exists. The portfolio must carry organization.revenue_eur for EUR values; initiatives with missing revenue or invalid taxonomy are reported as skipped, never silently counted. Run validate_portfolio first only when the document shape is uncertain, then call sequence_portfolio when the verdicts need turning into a 90-day order. Deterministic calculation with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.recommend_improvementsTurn 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. resistance_type selects the will or skill route, risk_type selects the regulatory, reputational or operational route, and omitted diagnostics remain provisional with the next question returned. Lead with binding_constraint, surface honest_stop when present, and use rescore_gate to decide whether this remains Fix or becomes Stop. Deterministic calculation with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.calculate_pace_layer_dragQuantify 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 EUR range; ai_tier and readiness together set the drag rate and pace_gap, so gen3 in a siloed organisation costs more than gen1 in an agile one. industry is accepted for a consistent interface and defaults to universal, but does not change this calculation yet. Returns a low/high EUR range, drag rate, pace-gap severity, drivers and source. Deterministic calculation with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.validate_portfolioCheck 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_portfolio when the document is already ready for verdicts, and sequence_portfolio only after its initiatives are scoreable. Returns valid=true or one error per failing JSON path. Deterministic validation with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.get_benchmarkLook 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 verdict or EUR business case. Replace it with measured organisation evidence before funding. Use score_initiative for an Accelerate/Fix/Stop decision, score_portfolio for several initiatives and diagnose_process for measured operational waste. Deterministic lookup with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.list_taxonomyReturn 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. Deterministic lookup with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.diagnose_processDiagnose 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, many hand-offs or wait to Consolidate & re-sequence, rework to Quality controls, low-volume heavy work to Eliminate / insource. signal_completeness must fall when inputs are estimated, because it directly reduces decision score. Use score_initiative for a proposed AI investment and infer_readiness when the question is the organisation’s change capacity. Effectiveness bands are benchmark-cited and figures are directional, not audited. Deterministic calculation with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.infer_readinessMeasure 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 returned gap exposes where its self-image runs ahead of the process data. Fewer than two signals produces a refusal, not a guess. Pass the measured readiness into the downstream tool, then use diagnose_process when the next question is what to change in that process. Deterministic calculation with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.sequence_portfolioTurn 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; both score shapes are accepted and nested values are flattened. readiness sets capture rates and pacing, max_parallel_per_function caps simultaneous change in one function per wave, and horizon_days divides the plan into three equal windows. Capacity overflow is reported as a conflict or a deferral beyond the horizon, never hidden. Run recommend_improvements for a Fix before treating its wave placement as permission to proceed. Deterministic calculation with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.map_to_taxonomyMap 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_benchmark or the portfolio tools. Deterministic lookup with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.- +1 more on the listing page
Cpm Planner tools 25
plan.release.compileCompile version-1 bounded release metadata into an ordinary lint-clean PlanGraph. Expands protected PR/check/approval/merge hops, producer retries, retained receipts and central acceptance. Every collection declares cardinality or a bounded retained source. Pure offline operation: never executes, accepts, submits or baselines work.plan.release.diffCompare a retained compiled graph with current version-1 workflow/promotion policy. Reports policy_changed, added/removed/changed ids and stale; includes retained-history estimate drift. Read-only: apply accepted changes through normal plan.sync or plan.revise.plan.submitSubmit a plan graph and receive a plan_id. Idempotent: identical graphs return the same plan_id. With `name` (and optional `project`/`variant`, variant defaults to "main"), registers a named variant instead: project defaults to the discovered project root.plan.acquire_cohortAcquire up to max_count ready deliverables with no conflicting file claims atomically. Returns the cohort plus per-deliverable locks. A deliverable explicitly marked failed 3 times is circuit-broken to failed instead of re-leased; leases lost environmentally (TTL lapse, no terminal mark) never trip that breaker but are bounded separately (LAPSE_LIMIT at 10). Optional ttl_seconds sets the lease TTL (clamped to the server maximum). Optional ids targets specific deliverables and filter.metadata narrows by metadata equality; deliverables with metadata.kind = "manual" are never leased. ids that do not match filter.metadata are ignored (not reported in blocked). The response carries blocked [{id, code, reason}], blocked_count, and needs_operator (true when any blocked code is LAPSE_LIMIT: clear with plan.force_release {reset_counters: true}). Select the plan by plan_id, plan line name, or active: true.plan.heartbeatRefresh the TTL on a held lock; LOCK_NOT_HELD or LOCK_EXPIRED on failure. Optional ttl_seconds sets the new TTL (clamped to the server maximum); without it the lease is never shortened. Select the plan by plan_id, plan line name, or active: true.plan.mark_statusSet a deliverable's status. Complete/Failed releases the lock; caller_id mismatch yields LOCK_NOT_HELD. Without a lock, Complete, Ready or InProgress requires all prerequisites complete (PREREQUISITES_INCOMPLETE) and is audited; other lockless marks are audited too, and an already-complete deliverable cannot be changed (LOCK_NOT_HELD). A lockless in_progress persists across restarts and is not leasable; hand it back with a lockless ready (or other status) mark. plan.force_release does not affect it. Optional earned-value progress: earned_pct (0..100, only with in_progress; ignored with complete), actual_effort_hours (total so far, 0..1000000; replaces leased hours as actual cost) and evidence (<= 2048 chars, appended to a list of at most 100); violations are INVALID_ACTUALS. Every lease that ends adds its hours to the deliverable's leased hours. Select the plan by plan_id, plan line name, or active: true.plan.statusRead-only snapshot: per-deliverable [id, status, attempt_count, failure_count, lapse_count] rows, critical_path (one real chain, always from __start__ to __finish__), critical_ids, per-deliverable schedule (es/ef/ls/lf/float, hours; synthetic __start__/__finish__ rows have synthetic=true), the ready set in float-ascending order (smallest float first, then smallest latest start, then id), plan_complete, milestones (per milestone: id, critical_path from __start__, hours, complete), and held locks. Select the plan by plan_id, plan line name, or active: true.plan.getReturn the stored PlanGraph (deliverables, estimates, files, metadata) for a plan selected by plan_id, plan line name, or active: true.plan.force_releaseOperator escape hatch — release a lock regardless of caller. Emits an audit event carrying `reason`. Select the plan by plan_id, plan line name, or active: true.plan.acceptManager/owner acceptance: mark a deliverable Complete without holding its lease. Requires all prerequisites Complete and evidence; audited. A live lease held by someone else is refused (LOCK_HELD) unless override_lock is true. Select the plan by plan_id, plan line name, or active: true.plan.lintLint a graph, stored plan, or plan file without creating one: cycles (with the loop), redundant edges, edges without rationale, interface edges not targeting a contract, deliverables feeding no milestone, and unordered file overlaps. Linting by plan_id also adds NO_BASELINE (warning) when the plan is executable and has recorded progress but no earned-value baseline. Provide exactly one of graph, plan_id, or path.plan.scheduleLevel a graph or stored plan against resource capacities (`metadata.owner` by default; metadata.resources can claim several pools concurrently): makespan, per-deliverable start/finish, per-resource load, the driving chain (dependency vs named resource waits), and project/feeding buffers. A deliverable with duration_hours plus metadata.wall_clock_only:true advances elapsed time but consumes no capacity. Provide exactly one of graph or plan_id. capacities is required: every resource that carries work needs at least 1 unit (otherwise INVALID_CAPACITIES: lists the missing resources). plan.schedule rejects what plan.submit rejects (INVALID_GRAPH:).- +13 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Aibvf MCP
{
"mcpServers": {
"aibvf-mcp-2": {
"command": "npx",
"args": [
"-y",
"aibvf-mcp"
]
}
}
}
Cpm Planner
{
"mcpServers": {
"cpm-planner": {
"command": "npx",
"args": [
"-y",
"@matthew-cochran/cpm"
],
"env": {
"CPM_PLANNER_DB": "YOUR_CPM_PLANNER_DB_HERE"
}
}
}
}
Frequently asked questions
Aibvf MCP is categorized under Product Management and uses a local stdio subprocess. Cpm Planner belongs to Product Management and uses a local stdio subprocess. Pick Aibvf MCP for product management work and Cpm Planner for product management.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Aibvf MCP has no declared pricing — check the project's own site. Cpm Planner is listed as free. Auth: no auth required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add aibvf-mcp-2 and cpm-planner as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Aibvf MCP has a quality signal of 61/100 (Good) with 1 views, 0 installs and 0 GitHub stars. Cpm Planner has 63/100 (Good) with 0 views, 0 installs and 0 GitHub stars.