# Agrus.ai — Enterprise AI Agency (remote · mcp.agrus.ai)

AI consulting agency for regulated industries. Scope a PoC, query compliance, request a proposal.

- Trust score: 68/100 (medium)
- Change this week: +5
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `mcp.agrus.ai`: 68/100 (this document), [markdown](https://verifymcp.io/servers/phwizard-mcp-agrus-ai/mcp.md), [page](https://verifymcp.io/servers/phwizard-mcp-agrus-ai/mcp)

## Channel facts

- Endpoint: `https://mcp.agrus.ai/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `0.2.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Endpoint Security**: 63/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation not fully verified: no authorisation is required to call this server, and 7 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe.
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 68/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 1183 tokens (~169/item across 7 items; 7 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add --transport http phwizard-mcp-agrus-ai https://mcp.agrus.ai/mcp
```

### Codex

```toml
[mcp_servers.phwizard-mcp-agrus-ai]
url = "https://mcp.agrus.ai/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "phwizard-mcp-agrus-ai": {
      "type": "remote",
      "url": "https://mcp.agrus.ai/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add phwizard-mcp-agrus-ai --url https://mcp.agrus.ai/mcp --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  phwizard-mcp-agrus-ai:
    url: "https://mcp.agrus.ai/mcp"
```

### Other

```json
{
  "mcpServers": {
    "phwizard-mcp-agrus-ai": {
      "type": "http",
      "url": "https://mcp.agrus.ai/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-03 (score 68, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-08-01 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-31 (score 66, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 65, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-29 (score 65, +1)

No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-28 (score 64, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-27 (score 63, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-26 (score 63)

First indexed and scored.

## MCP tools (7)

### `list_services` (~79 tokens)

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.

Input parameters:

- `vertical` (string): Filter services by vertical applicability. Currently all services apply to all verticals.

### `list_verticals` (~65 tokens)

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.

### `query_compliance_position` (~195 tokens)

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.

Input parameters:

- `data_types` (array): Optional list of data types the AI would touch (e.g. ['PHI', 'PII', 'claims data', 'underwriting decisions']).
- `regime` (string, required): Which regulatory regime to query Agrus's position on.
- `use_case` (string, required): 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').

### `get_case_study` (~108 tokens)

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.

Input parameters:

- `slug` (string): Specific case-study slug. If omitted, returns all available case studies (filtered by vertical if provided).
- `vertical` (string): Filter case studies by vertical. Ignored if slug is provided.

### `scope_poc` (~249 tokens)

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.

Input parameters:

- `compliance_constraints` (array): Regulatory regimes the deployment must satisfy. Drives compliance overlay in the scope.
- `data_types` (array): Data the AI would touch (e.g. ['PHI', 'patient demographics', 'EHR notes']).
- `target_outcomes` (array): What success looks like (e.g. ['reduce adjuster review time by 50%', 'production pilot with 3 clinicians by Q3']).
- `timeline_hint` (string): Free-form timeline (e.g. 'exploring', 'this quarter', 'production by Q4', 'this is blocking board commitment').
- `use_case` (string, required): 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` (string, required): Which Agrus vertical the use case sits in.

### `request_quote` (~173 tokens)

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.

Input parameters:

- `compliance_constraints` (array): Regulatory regimes the deployment must satisfy. Drives the compliance overlay on the quote.
- `summary` (string, required): Two or three sentences describing the AI deployment the buyer wants a ballpark quote for. Include workflow, users, and integration surface where possible.
- `urgency` (string): Free-form timeline indicator.
- `vertical` (string, required): Which Agrus vertical the use case sits in.

### `request_proposal` (~314 tokens)

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.

Input parameters:

- `company` (string, required): Company / organization name.
- `compliance_constraints` (array): Regulatory regimes the deployment must satisfy.
- `contact_email` (string, required): Work email of the buyer (or buyer's assistant) who should receive the formal proposal.
- `contact_name` (string, required): Full name of the contact. Example: 'Jane Doe'.
- `persona_context` (string): 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>').
- `role` (string): Buyer's role at the company (e.g. 'CIO', 'Head of AI', 'Managing Partner').
- `scope_summary` (string, required): One to three paragraphs describing the proposed AI deployment: workflow, users, data, integration surface, success criteria.
- `urgency` (string): How quickly the buyer wants to move.
- `vertical` (string, required): Which Agrus vertical the use case sits in.

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/phwizard-mcp-agrus-ai/mcp#diagnostics

## Score history

- 2026-08-03: 68
- 2026-08-02: 67
- 2026-08-01: 67
- 2026-07-31: 66
- 2026-07-30: 65
- 2026-07-29: 65
- 2026-07-28: 64
- 2026-07-27: 63
- 2026-07-26: 63

## Links

- Remote endpoint: https://mcp.agrus.ai/mcp
- Repository: https://github.com/phwizard/mcp-agrus-ai
- Changelog RSS feed: https://verifymcp.io/servers/phwizard-mcp-agrus-ai/mcp/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/phwizard-mcp-agrus-ai/mcp/changelog.json
- HTML version of this page: https://verifymcp.io/servers/phwizard-mcp-agrus-ai/mcp