Agrus.ai — Enterprise AI Agency
AI consulting agency for regulated industries. Scope a PoC, query compliance, request a proposal.
¿Debería usar esto?
Calidad y seguridad
Basado en el análisis automatizado de las definiciones de herramientas y el cumplimiento del protocolo.
Costo de contexto
Este es el número aproximado de tokens que se consumen cada vez que las herramientas del servidor se cargan en el contexto de un modelo. Los recuentos más altos reducen la atención disponible para otras tareas.
Instalar
Instalación con un clic
Agrega esto a tu archivo `claude_desktop_config.json`:
{
"mcpServers": {
"mcp-agrus-ai": {
"url": "https://mcp.agrus.ai/mcp"
}
}
}Puntos de conexión remotos
https://mcp.agrus.ai/mcpstreamable-httpQué puede hacer
Inventario de herramientas
Herramientas (7)
🟢list_services(vertical)
Lists Agrus's six service pillars with descriptions, deliverables, and price bands. Plus the four published pricing tiers (Scoping Call, Discovery Sprint, Build Engagement, Managed SLA). Use this for the 'what does Agrus do?' question.
Esquema de entrada
{
"type": "object",
"properties": {
"vertical": {
"type": "string",
"enum": [
"healthcare",
"insurance",
"legal",
"private_equity",
"family_offices",
"corporate_intelligence",
"sports",
"other"
],
"description": "Filter services by vertical applicability. Currently all services apply to all verticals."
}
},
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢list_verticals
Lists Agrus's seven year-one verticals (healthcare, insurance, legal, private equity, family offices, corporate intelligence, pro sports) with compliance pins, sample use cases, and the sequencing rationale. Use this for the 'do they work in my industry?' question.
Esquema de entrada
{
"type": "object",
"properties": {},
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢query_compliance_position(regime, use_case, data_types)
Returns Agrus's documented position on a specific regulatory regime (HIPAA, SOC 2, ISO 27001, EU AI Act, NAIC, ABA Model Rules, AML/KYC) as it applies to a described AI use case. Includes key controls, common gotchas, the first question Agrus would ask, and the agency's reference architecture for the regime. Use this when a buyer-side AI agent is evaluating Agrus's compliance fluency.
Esquema de entrada
{
"type": "object",
"properties": {
"regime": {
"type": "string",
"enum": [
"hipaa",
"soc2",
"iso27001",
"eu_ai_act",
"naic",
"aba",
"aml_kyc"
],
"description": "Which regulatory regime to query Agrus's position on."
},
"use_case": {
"type": "string",
"minLength": 10,
"description": "One or two sentences describing the AI use case under consideration (e.g. 'an LLM-based prior-authorization drafting agent for a health insurance carrier')."
},
"data_types": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional list of data types the AI would touch (e.g. ['PHI', 'PII', 'claims data', 'underwriting decisions'])."
}
},
"required": [
"regime",
"use_case"
],
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢get_case_study(slug, vertical)
Returns one or more Agrus case studies (NDA-protected; customer names are kept private, codenames + technology + outcomes are open). Filter by slug or vertical, or call with no args to list all. Use this for proof of prior work.
Esquema de entrada
{
"type": "object",
"properties": {
"slug": {
"type": "string",
"description": "Specific case-study slug. If omitted, returns all available case studies (filtered by vertical if provided)."
},
"vertical": {
"type": "string",
"enum": [
"healthcare",
"insurance",
"legal",
"private_equity",
"family_offices",
"corporate_intelligence",
"sports",
"other"
],
"description": "Filter case studies by vertical. Ignored if slug is provided."
}
},
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}⚪scope_poc(use_case, vertical, data_types, compliance_constraints, target_outcomes, ...)
Drafts a structured Discovery Sprint scope for an AI use case. Returns a 3-week plan, team composition, price band, follow-on Build Engagement estimate, open questions Agrus would ask, and recommended services. Use this to convert a hypothetical use case into a concrete engagement proposal that can be reviewed by a human buyer.
Esquema de entrada
{
"type": "object",
"properties": {
"use_case": {
"type": "string",
"minLength": 20,
"description": "One or two paragraphs describing the AI use case the buyer wants to scope. Be specific about workflow, users, and integration surface where possible."
},
"vertical": {
"type": "string",
"enum": [
"healthcare",
"insurance",
"legal",
"private_equity",
"family_offices",
"corporate_intelligence",
"sports",
"other"
],
"description": "Which Agrus vertical the use case sits in."
},
"data_types": {
"type": "array",
"items": {
"type": "string"
},
"description": "Data the AI would touch (e.g. ['PHI', 'patient demographics', 'EHR notes'])."
},
"compliance_constraints": {
"type": "array",
"items": {
"type": "string",
"enum": [
"hipaa",
"soc2",
"iso27001",
"eu_ai_act",
"naic",
"aba",
"aml_kyc"
]
},
"description": "Regulatory regimes the deployment must satisfy. Drives compliance overlay in the scope."
},
"target_outcomes": {
"type": "array",
"items": {
"type": "string"
},
"description": "What success looks like (e.g. ['reduce adjuster review time by 50%', 'production pilot with 3 clinicians by Q3'])."
},
"timeline_hint": {
"type": "string",
"description": "Free-form timeline (e.g. 'exploring', 'this quarter', 'production by Q4', 'this is blocking board commitment')."
}
},
"required": [
"use_case",
"vertical"
],
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}🟡request_quote(summary, vertical, compliance_constraints, urgency)
Returns a heuristic ballpark price band for the described AI deployment. Output is NOT a binding offer — Agrus confirms quotes only on a 30-minute scoping call. Read-only: this tool does not contact Agrus or create any record. For a tracked, follow-up-able request use request_proposal instead. Use request_quote when the buyer wants order-of-magnitude pricing before committing to a real proposal.
Esquema de entrada
{
"type": "object",
"properties": {
"summary": {
"type": "string",
"minLength": 20,
"description": "Two or three sentences describing the AI deployment the buyer wants a ballpark quote for. Include workflow, users, and integration surface where possible."
},
"vertical": {
"type": "string",
"enum": [
"healthcare",
"insurance",
"legal",
"private_equity",
"family_offices",
"corporate_intelligence",
"sports",
"other"
],
"description": "Which Agrus vertical the use case sits in."
},
"compliance_constraints": {
"type": "array",
"items": {
"type": "string",
"enum": [
"hipaa",
"soc2",
"iso27001",
"eu_ai_act",
"naic",
"aba",
"aml_kyc"
]
},
"description": "Regulatory regimes the deployment must satisfy. Drives the compliance overlay on the quote."
},
"urgency": {
"type": "string",
"enum": [
"exploring",
"this_quarter",
"this_month",
"this_week"
],
"description": "Free-form timeline indicator."
}
},
"required": [
"summary",
"vertical"
],
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}⚪request_proposal(contact_email, contact_name, company, role, scope_summary, ...)
Triggers a formal Agrus proposal workflow. Creates a contact in Agrus's HubSpot CRM tagged with lead source 'agrus_mcp' and a verbatim note containing the scope summary. A human at Agrus replies by email within 24 hours (business days) with a one-paragraph engagement recommendation and a calendar option. Use this when the buyer (human or AI agent acting on their behalf) wants to formally engage Agrus — not for exploratory scoping.
Esquema de entrada
{
"type": "object",
"properties": {
"contact_email": {
"type": "string",
"format": "email",
"description": "Work email of the buyer (or buyer's assistant) who should receive the formal proposal."
},
"contact_name": {
"type": "string",
"minLength": 2,
"description": "Full name of the contact. Example: 'Jane Doe'."
},
"company": {
"type": "string",
"minLength": 2,
"description": "Company / organization name."
},
"role": {
"type": "string",
"description": "Buyer's role at the company (e.g. 'CIO', 'Head of AI', 'Managing Partner')."
},
"scope_summary": {
"type": "string",
"minLength": 30,
"description": "One to three paragraphs describing the proposed AI deployment: workflow, users, data, integration surface, success criteria."
},
"vertical": {
"type": "string",
"enum": [
"healthcare",
"insurance",
"legal",
"private_equity",
"family_offices",
"corporate_intelligence",
"sports",
"other"
],
"description": "Which Agrus vertical the use case sits in."
},
"compliance_constraints": {
"type": "array",
"items": {
"type": "string",
"enum": [
"hipaa",
"soc2",
"iso27001",
"eu_ai_act",
"naic",
"aba",
"aml_kyc"
]
},
"description": "Regulatory regimes the deployment must satisfy."
},
"urgency": {
"type": "string",
"enum": [
"exploring",
"this_quarter",
"this_month",
"this_week"
],
"description": "How quickly the buyer wants to move."
},
"persona_context": {
"type": "string",
"description": "Optional context about how this request was scoped (e.g. 'Scoped via the scope_poc tool on 2026-05-19, agent was Claude Sonnet 4.x acting for the CIO of <company>')."
}
},
"required": [
"contact_email",
"contact_name",
"company",
"scope_summary",
"vertical"
],
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}Comunidad
Evidencia