craft-gtm-mcp
https://craft-gtm.gtmhelix.com
Registry code: f6ce8c3b4f8f58c3
CRAFT GTM: 8 go to market strategy tools by Helix GTM Consulting
from a public catalogue that lists it, not from the operator
- endpoint
- https://craft-gtm.gtmhelix.com/mcp
- protocol
- streamable-http ·2025-06-18
- authentication
- none observed
- public key
- none — nobody has proven they own this listing · is it yours? claim it
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- 0 · newcomer
- Is craft-gtm-mcp live?
- Yes — it answered the hub's last check (checked 2h ago). It answered 100% of checks over the last 30 days.
- Is craft-gtm-mcp free to use?
- Yes — the hub reached it with no key and no payment.
- What tools does craft-gtm-mcp have?
- 8 tools: pmf_scorecard, launch_commander, customer_interview_kit, retention_playbook, partner_architect, competitive_intel, craft_gtm_analyzer, crisis_planner.
- Is craft-gtm-mcp safe to connect?
- The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
90 days 100%· all time 100%
last good check
of 8 tools
- unknown → live
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successful
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Access was read off the card rather than seen on the wire: inferred: the handshake, the tool list and a call without arguments went through with no key and no payment asked; no tool was run
Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.
pmf_scorecard unknown never probed
Takes your product, target market and current metrics (MRR, ACV, churn, NPS, CAC, LTV, retention, activation and similar) and returns a product-market fit scorecard that scores each dimension against example benchmark ranges. Reads the business model from your inputs and leaves the activation score out for services, connectivity and investment businesses. Quotes your customer feedback and answers it.
{ "type": "object", "required": [ "product", "target_market", "current_metrics" ], "properties": { "product": { "type": "string", "description": "Product name and brief description" }, "your_sector": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: your company's own industry (not your customers'). When given, it decides the sector notes; when left out, the tool reads it from your words and stays neutral if they are unclear." }, "target_market": { "enum": [ "enterprise_saas", "smb_saas", "consumer", "marketplace", "fintech", "logistics_tech", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Target market segment (for example enterprise SaaS, telecom or logistics tech)" }, "business_model": { "enum": [ "saas", "services", "connectivity", "transactions", "marketplace", "hardware_software", "investment" ], "type": "string", "description": "Optional: how you earn revenue, so the advice fits it (saas, services, connectivity, transactions, marketplace, hardware_software or investment). Leave it out and the tool reads it from your other inputs and says how it read it" }, "time_in_market": { "enum": [ "pre_launch", "0_6_months", "6_12_months", "1_2_years", "2_plus_years" ], "type": "string", "description": "How long the product has been in market (shown in the scorecard)" }, "current_metrics": { "type": "string", "description": "Your current metrics, written as text (the tool reads the figures from it). Include any of: MRR, ARR, ACV, churn rate, NPS, CAC, LTV, retention rate, activation rate, DAU/MAU, trial conversion, revenue growth. Example: 'MRR: $50K, Churn: 3%, NPS: 45, CAC: $500, LTV: $3000, Retention: 92%'. A figure that no rule scores is listed as not scored" }, "customer_feedback": { "type": "string", "description": "Optional: Qualitative feedback themes, one per line or separated by semicolons (for example 'Customers like X; they struggle with Y'). Each theme is quoted and answered" } } }arguments 81 lineslaunch_commander unknown never probed
Takes what you are launching, the launch type, your target segments and your goals, and returns a phased launch plan with tasks, a messaging table and success metrics. Give a date for a dated timeline, or enter 'TBD' or a quarter such as 'Q2 2027' for a flexible plan. Tasks and the messaging table follow the sector and business model read from your inputs, and each goal is filed under its own metric.
{ "type": "object", "required": [ "product_feature", "launch_type", "target_segments", "goals" ], "properties": { "goals": { "type": "string", "description": "Launch success metrics (for example '40 qualified meetings, $300K pipeline, 5 reference customers')" }, "industry": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: the sector you sell into, so the answer uses that sector's buyers, measures and objections. Leave it out and the tool reads the sector from your other inputs and names what it read" }, "team_size": { "enum": [ "solo", "small_2_5", "medium_6_15", "large_15_plus" ], "type": "string", "description": "Marketing/GTM team size affects task distribution" }, "launch_date": { "type": "string", "description": "Target launch date. Accepts: 'YYYY-MM-DD', 'Q1 2027', 'March 2027', or 'TBD' for planning mode" }, "launch_type": { "enum": [ "major_release", "feature_launch", "beta_launch", "product_update", "market_expansion" ], "type": "string", "description": "Type of launch determines plan complexity" }, "your_sector": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: your company's own industry (not your customers'). When given, it decides the sector notes; when left out, the tool reads it from your words and stays neutral if they are unclear." }, "budget_level": { "enum": [ "bootstrap", "moderate", "well_funded" ], "type": "string", "description": "Budget affects recommended tactics" }, "business_model": { "enum": [ "saas", "services", "connectivity", "transactions", "marketplace", "hardware_software", "investment" ], "type": "string", "description": "Optional: how you earn revenue, so the advice fits it (saas, services, connectivity, transactions, marketplace, hardware_software or investment). Leave it out and the tool reads it from your other inputs and says how it read it" }, "product_feature": { "type": "string", "description": "What you're launching (product/feature name and description)" }, "target_segments": { "type": "string", "description": "Target customer segments (comma-separated)" }, "available_channels": { "type": "string", "description": "Optional: Marketing channels available (comma-separated). E.g., 'email, linkedin, blog, webinar, PR, paid_ads, community'" } } }arguments 106 linescustomer_interview_kit unknown never probed
Takes the interview type, the product context and the person you are interviewing, and returns an interview guide that fits the interview type, the sector (chosen, or read from your inputs) and the product complexity. Questions use the sector's own language, your hypotheses are kept whole, and synthesis templates are included.
{ "type": "object", "required": [ "interview_type", "product_context", "target_persona" ], "properties": { "industry": { "enum": [ "saas", "fintech", "logistics_tech", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "ecommerce", "marketplace", "enterprise_software", "consumer", "other" ], "type": "string", "description": "Industry affects terminology and context. Leave it out and the sector is read from your other inputs" }, "your_sector": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: your company's own industry (not your customers'). When given, it decides the sector notes; when left out, the tool reads it from your words and stays neutral if they are unclear." }, "business_model": { "enum": [ "saas", "services", "connectivity", "transactions", "marketplace", "hardware_software", "investment" ], "type": "string", "description": "Optional: how you earn revenue, so the advice fits it (saas, services, connectivity, transactions, marketplace, hardware_software or investment). Leave it out and the tool reads it from your other inputs and says how it read it" }, "interview_type": { "enum": [ "discovery", "validation", "feedback", "churn", "win_loss", "persona_research" ], "type": "string", "description": "Type of interview determines question focus" }, "key_hypotheses": { "type": "string", "description": "Optional: Hypotheses to validate during interview, one per line or separated by semicolons" }, "target_persona": { "type": "string", "description": "Who you're interviewing (role/title)" }, "product_context": { "type": "string", "description": "Product/service being researched" }, "product_complexity": { "enum": [ "simple", "moderate", "complex", "highly_technical" ], "type": "string", "description": "Affects technical depth of questions" } } }arguments 93 linesretention_playbook unknown never probed
Takes your customer segment, business model and current churn rate, and returns a retention playbook with health signals, interventions and an email draft for each churn reason. If you do not know why customers leave, leave the churn reasons out and you get a churn discovery kit with a framework for finding out. Health signals and interventions follow the business model, each churn reason gets its own answer, and your current interventions and data signals are used.
{ "type": "object", "required": [ "customer_segment", "business_model", "current_churn_rate" ], "properties": { "product": { "type": "string", "description": "Optional: Your product or company name, used in the title and the email drafts" }, "industry": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: the sector you sell into, so the answer uses that sector's buyers, measures and objections. Leave it out and the tool reads the sector from your other inputs and names what it read" }, "your_sector": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: your company's own industry (not your customers'). When given, it decides the sector notes; when left out, the tool reads it from your words and stays neutral if they are unclear." }, "cs_team_size": { "enum": [ "no_dedicated_cs", "small_1_3", "medium_4_10", "large_10_plus" ], "type": "string", "description": "CS team capacity affects intervention strategy" }, "churn_reasons": { "type": "string", "description": "Optional: known churn reasons, comma-separated. If you do not know them, leave this blank and you get a churn discovery kit with a framework for finding the reasons" }, "business_model": { "enum": [ "saas_subscription", "usage_based", "marketplace", "transactional", "freemium", "enterprise_contract", "services_contract", "connectivity_contract", "investment_mandate" ], "type": "string", "description": "Business model affects health score weighting. enterprise_contract is read further from your text when it names services, connectivity or investment" }, "customer_segment": { "type": "string", "description": "Customer segment to focus on" }, "current_churn_rate": { "type": "string", "description": "Current churn rate (e.g., '5%' or '5% monthly')" }, "current_interventions": { "type": "string", "description": "Optional: What retention tactics you already do (listed and compared with the playbook)" }, "available_data_signals": { "type": "string", "description": "What you can track (comma-separated). E.g., 'login frequency, support tickets, SLA attainment, QBR attendance'" } } }arguments 91 linespartner_architect unknown never probed
Takes your company, product, partner model, partner goal and deal size, and returns a partner program with tiers, example commission amounts and KPIs, with a different structure for resellers, referrals, integrations, agencies, affiliates and white label. Uses your stated goal, existing partners and deal size, and names the partner types that fit your sector's buying committee.
{ "type": "object", "required": [ "company", "product", "partner_model", "partner_goals", "your_deal_size" ], "properties": { "company": { "type": "string", "description": "Your company name" }, "product": { "type": "string", "description": "Product partners will sell/integrate" }, "industry": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: the sector you sell into, so the answer uses that sector's buyers, measures and objections. Leave it out and the tool reads the sector from your other inputs and names what it read" }, "your_sector": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: your company's own industry (not your customers'). When given, it decides the sector notes; when left out, the tool reads it from your words and stays neutral if they are unclear." }, "partner_goals": { "type": "string", "description": "Revenue/growth targets from partners (shown as the target of the first KPI row)" }, "partner_model": { "enum": [ "reseller", "referral", "integration_tech", "agency_si", "affiliate", "oem_white_label" ], "type": "string", "description": "Partner type determines program structure" }, "business_model": { "enum": [ "saas", "services", "connectivity", "transactions", "marketplace", "hardware_software", "investment" ], "type": "string", "description": "Optional: how you earn revenue, so the advice fits it (saas, services, connectivity, transactions, marketplace, hardware_software or investment). Leave it out and the tool reads it from your other inputs and says how it read it" }, "your_deal_size": { "type": "string", "description": "Average deal size as one amount (e.g., '$5000 ACV', '$5K' or '$500/month'; a range is refused). It scales the example commission amounts; the example rates are fixed" }, "existing_partners": { "type": "string", "description": "Optional: Current partner types/count, one per line or separated by semicolons (listed in the plan)" }, "partner_support_capacity": { "enum": [ "minimal_self_serve", "moderate", "high_touch" ], "type": "string", "description": "How much partner support can you provide?" } } }arguments 98 linescompetitive_intel unknown 2h ago
Takes your product and the competitors you name, and returns one battle card per competitor built from your strengths, weaknesses, competitor details, objections, wins and losses. Each competitor detail goes to the competitor it names, each objection gets its own answer, and strengths and gaps taken from wins and losses are your own words.
{ "type": "object", "required": [ "your_product", "competitors" ], "properties": { "industry": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: the sector you sell into, so the answer uses that sector's buyers, measures and objections. Leave it out and the tool reads the sector from your other inputs and names what it read" }, "competitors": { "type": "string", "description": "Competitor names, comma-separated. You get one battle card for each competitor named" }, "recent_wins": { "type": "string", "description": "Why customers chose you over competitors: used as your strengths when none are given" }, "your_sector": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: your company's own industry (not your customers'). When given, it decides the sector notes; when left out, the tool reads it from your words and stays neutral if they are unclear." }, "your_product": { "type": "string", "description": "Your product name and brief description" }, "recent_losses": { "type": "string", "description": "Why you lost deals to competitors: used as your gaps when none are given" }, "business_model": { "enum": [ "saas", "services", "connectivity", "transactions", "marketplace", "hardware_software", "investment" ], "type": "string", "description": "Optional: how you earn revenue, so the advice fits it (saas, services, connectivity, transactions, marketplace, hardware_software or investment). Leave it out and the tool reads it from your other inputs and says how it read it" }, "your_strengths": { "type": "string", "description": "Optional: what you do better, comma-separated. Taken from your wins, in your own words, if not provided" }, "your_weaknesses": { "type": "string", "description": "Optional: where competitors beat you, comma-separated. Taken from your losses, in your own words, if not provided" }, "common_objections": { "type": "string", "description": "Sales objections you hear (comma-separated). E.g., 'too expensive, missing X feature, competitor has better Y'" }, "competitor_details": { "type": "string", "description": "Optional: Any known details about competitors, one per line or separated by semicolons. E.g., 'Competitor A is cheaper; Competitor B targets enterprise'. Each detail goes to the competitor it names" } } }arguments 86 linescraft_gtm_analyzer unknown 2h ago
Takes the text of a GTM document or plan and returns an analysis against the CRAFT framework, with a score for each dimension. Each dimension is scored only on what the plan contains (Timeline counts real dates, durations and quarters), the tool shows the plan's own line for each, names only the elements that are missing and suggests sections to add.
{ "type": "object", "required": [ "document_content", "document_type" ], "properties": { "industry": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: the sector you sell into, so the answer uses that sector's buyers, measures and objections. Leave it out and the tool reads the sector from your other inputs and names what it read" }, "your_sector": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: your company's own industry (not your customers'). When given, it decides the sector notes; when left out, the tool reads it from your words and stays neutral if they are unclear." }, "document_type": { "enum": [ "gtm_strategy", "launch_plan", "campaign_brief", "quarterly_plan", "project_proposal", "marketing_plan" ], "type": "string", "description": "Type of document (shown in the analysis)" }, "desired_outcome": { "type": "string", "description": "Optional: What action should this document drive" }, "document_content": { "type": "string", "description": "The GTM document or plan to analyze. Paste the full text: the tool reads it and scores it against the framework" }, "intended_audience": { "type": "string", "description": "Optional: Who will read/approve this document" } } }arguments 65 linescrisis_planner unknown 2h ago
Takes your company, industry, customer base and data sensitivity, and returns crisis playbooks with a response team and notification steps for each crisis. Name the crises you know of to get those playbooks. If you leave them out, the tool uses a default set of common crises for your sector (not ranked by likelihood). Each compliance item you list is used in the notification steps.
{ "type": "object", "required": [ "company", "industry", "customer_base", "data_sensitivity" ], "properties": { "company": { "type": "string", "description": "Company name" }, "industry": { "enum": [ "fintech", "saas", "logistics_tech", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "ecommerce", "enterprise", "consumer", "other" ], "type": "string", "description": "Industry affects which crises to prioritize" }, "your_sector": { "enum": [ "logistics_tech", "fintech", "saas", "vertical_saas", "ai_native", "ites", "telecom", "software", "cybersecurity", "other" ], "type": "string", "description": "Optional: your company's own industry (not your customers'). When given, it decides the sector notes; when left out, the tool reads it from your words and stays neutral if they are unclear." }, "company_size": { "enum": [ "startup_under_50", "scaleup_50_200", "midsize_200_1000", "enterprise_1000_plus" ], "type": "string", "description": "Affects response team structure" }, "customer_base": { "enum": [ "b2b_enterprise", "b2b_smb", "b2c_consumer", "mixed" ], "type": "string", "description": "Customer type affects communication approach" }, "business_model": { "enum": [ "saas", "services", "connectivity", "transactions", "marketplace", "hardware_software", "investment" ], "type": "string", "description": "Optional: how you earn revenue, so the advice fits it (saas, services, connectivity, transactions, marketplace, hardware_software or investment). Leave it out and the tool reads it from your other inputs and says how it read it" }, "data_sensitivity": { "enum": [ "high_pii_financial", "medium_business_data", "low_general" ], "type": "string", "description": "Data sensitivity affects security protocols" }, "potential_crises": { "type": "string", "description": "Optional: crisis types to plan for, comma-separated. If not provided, the tool uses a default set of common crises for your sector (not ranked by likelihood). Options: data_breach, service_outage, sla_breach, regulatory_action, fraud_incident, ai_wrong_action, pr_incident, executive_departure, security_vulnerability, customer_data_exposure, product_safety" }, "compliance_requirements": { "type": "string", "description": "Optional: Relevant compliance, comma-separated (for example ISO 27001, SOC 2, GDPR). Each item is named in the notification steps" } } }arguments 100 lines
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GET /api/v1/me, thenPOST /api/v1/passport. - Prove it is yours. Easiest: put
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POST /api/v1/passport/claim-endpointwith this listing's idf6ce8c3b4f8f58c3.
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Served from the same domain, which is what was measured. Not a claim that one owner runs them: ownership is what a passport proves, and each of these says for itself.
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