Agrus.ai — Enterprise AI Agency

io.github.phwizard由 GitHub 账号 phwizard 发布v0.2.0更新于 Oct 27, 2026

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

已验证Streamable HTTP可网页运行知识与记忆商业与电商

概览

AI 生成的概览

让助手浏览 Agrus.ai 的 AI 咨询服务、行业方向、合规立场与案例,并可起草 PoC 范围或提交正式提案请求。

可以做什么
  • 列出 Agrus 的服务支柱、定价档位与目标行业及其合规要点
  • 针对所描述的用例,查询该机构对 HIPAA、SOC 2、ISO 27001、EU AI Act、NAIC、ABA Model Rules、AML/KYC 等监管制度的书面立场
  • 按 slug 或行业获取受 NDA 保护的案例研究,或不带参数列出全部案例
  • 根据用例描述起草结构化的 Discovery Sprint 范围,含三周计划、团队构成、价格区间与待确认问题
  • 给出所描述部署的启发式价格区间,或触发正式提案流程并在其 CRM 中创建联系人
适用场景
适合买方一侧的助手调研面向受监管行业的 AI 咨询机构时使用,需要服务、行业、合规与案例信息,或在正式沟通前先获得初步 PoC 范围与价格区间。
运行要求
可使用 mcp.agrus.ai 的远程 Streamable HTTP 端点,或通过 npx 或源码本地以 stdio 运行,需 Node.js 20+ 及兼容 MCP 的客户端。只读工具未声明需要认证。
安装前请注意
request_proposal 是写入操作:会在 Agrus 的 HubSpot CRM 中创建标记为 agrus_mcp 来源的联系人并保存范围摘要原文,随后由人工邮件回复。request_quote 给出的价格区间不构成有约束力的报价。案例研究受 NDA 保护,客户名称不公开。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Agrus.ai — Enterprise AI Agency,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.phwizard%2Fmcp-agrus-ai/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "agrus-ai-enterprise-ai-agency": {
      "type": "http",
      "url": "https://mcp.agrus.ai/mcp"
    }
  }
}

README

mcp-agrus-ai

[Test] [License: MIT] [Node] [MCP]

A Model Context Protocol server for Agrus.ai — the front-deployed AI agency for regulated industries.

This server lets AI agents (Claude, ChatGPT, Gemini, custom buyer-side agents) engage Agrus.ai programmatically. A CIO using her internal Claude assistant can ask "find me a HIPAA-compliant AI consultancy that does self-hosted deployments and scope a 2-week PoC for clinical triage" — and that assistant can complete most of the workflow through this MCP server.

Currently ships 5 read-only tools (Phase 1). Write tools (book a call, request a proposal, request a quote) land in Phase 2 — see Roadmap.

Tools

ToolDescription
list_servicesSix service pillars + published pricing tiers (Scoping Call, Discovery Sprint $15-30K, Build T&M $200-280/hr, Managed SLA $4-15K/mo).
list_verticalsSeven year-one verticals (healthcare, insurance, legal, private equity, family offices, corporate intelligence, pro sports) with compliance pins and sequencing.
query_compliance_positionAgrus'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.
get_case_studyNDA-protected case studies — customer names private, codenames + tech + outcomes open.
scope_pocDrafts a full Discovery Sprint scope (3-week plan, team composition, price band, open questions, recommended services) from a use case description.

All tools return structured JSON inside an MCP text content block. No authentication required for Phase 1 tools.

Requirements

  • Node.js 20+ (uses ES modules + NodeNext resolution)
  • An MCP-compatible client (Claude Desktop, Continue.dev, Cursor, or anything that speaks the MCP stdio protocol)

Install

From source

bash
git clone https://github.com/phwizard/mcp-agrus-ai.gitcd mcp-agrus-ainpm installnpm run build

The built entry point is dist/index.js (executable, #!/usr/bin/env node shebang).

From npm

bash
npx -y mcp-agrus-ai

No global install needed. npx fetches the latest published version and runs it over stdio.

Three ways to use this server

1. Hosted (recommended)

The server is publicly hosted at https://mcp.agrus.ai/mcp (Streamable HTTP transport). No install required. Point any MCP client that supports remote URL transports at:

json
{  "mcpServers": {    "agrus": {      "url": "https://mcp.agrus.ai/mcp"    }  }}

2. Local stdio via npx

For Claude Desktop and other clients that prefer stdio:

json
{  "mcpServers": {    "agrus": {      "command": "npx",      "args": ["-y", "mcp-agrus-ai"]    }  }}

Claude Desktop config path on macOS: ~/Library/Application Support/Claude/claude_desktop_config.json.

3. Local stdio from source

For development against a local checkout:

json
{  "mcpServers": {    "agrus": {      "command": "node",      "args": ["/absolute/path/to/mcp-agrus-ai/dist/index.js"]    }  }}

Restart your MCP client after editing the config. The seven Agrus tools will be available in any conversation. Try:

Use the agrus MCP to query Agrus's position on HIPAA for an AI agent that drafts clinical notes against a patient's EHR.

Scope a Discovery Sprint with Agrus for an insurance carrier that wants AI-assisted claims triage with bias testing.

List Agrus's verticals and tell me which one a fintech regulatory-reporting copilot would fall into.

Use with other MCP clients

Anything that speaks MCP stdio or Streamable HTTP works. For remote use, the canonical endpoint is https://mcp.agrus.ai/mcp and the discovery manifest sits at https://mcp.agrus.ai/.well-known/mcp.json.

Test the server directly

Send raw MCP protocol messages over stdio:

bash
printf '%s\n' \  '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"test","version":"0.0.1"}}}' \  '{"jsonrpc":"2.0","method":"notifications/initialized"}' \  '{"jsonrpc":"2.0","id":2,"method":"tools/list","params":{}}' \  | node dist/index.js

You should see the protocol handshake and a JSON-RPC response listing all 7 tools (5 read + 2 write).

Development

bash
npm test            # run the full test suite once (~250ms, 86 tests)npm run test:watch  # watch mode for active developmentnpm run typecheck   # strict TypeScript check across src/ + api/npm run build       # compile to dist/npm run verify      # typecheck + test + build, in that order

The suite covers content integrity (slug uniqueness, enum coverage), each of the 7 tool handlers (happy paths + schema-rejection paths), the HubSpot client (mocked fetch exercising the upsert POST → 409-fallback GET → PATCH chain), and a full end-to-end MCP protocol handshake using the SDK's InMemoryTransport (verifies the same code that runs over stdio and over HTTP works in-process).

GitHub Actions runs npm run verify on every push to main and on every PR — see .github/workflows/test.yml.

Architecture

src/├── index.ts                          ← Entry point. McpServer + stdio transport.├── content/                          ← Source of truth for Agrus content.│   ├── services.ts                   ← 6 service pillars + descriptions.│   ├── verticals.ts                  ← 7 verticals + compliance pins.│   ├── compliance-regimes.ts         ← 7 regulatory regimes + Agrus position.│   ├── case-studies.ts               ← NDA-protected codenamed case studies.│   └── pricing.ts                    ← Published pricing tiers.└── tools/    ├── index.ts                      ← Tool registration table.    ├── list-services.ts    ├── list-verticals.ts    ├── query-compliance-position.ts    ├── get-case-study.ts    └── scope-poc.ts

Each tool defines a Zod inputSchema (a ZodRawShape) and a handler function returning MCP content. Tools are wired into the server via the registration table in tools/index.ts — adding a sixth tool means writing one new file + one entry in the registration table.

Why this exists

In 2026, more buyer research is done by AI agents acting on behalf of humans. A CIO using her internal Claude assistant can ask "find me three AI consultancies that do self-hosted HIPAA-compliant deployments and book intros." If we are MCP-discoverable, we participate in that conversation. If we aren't, we're invisible to that buyer type.

This is also the deepest layer of Agrus's brand differentiation: we are an AI agency that has invested in being engageable by AI agents. The MCP server is what we point to when prospects ask "are you AI-first or are you using the marketing term?"

Roadmap

Phase 1 (this release)

  • 5 read-only tools (list_services, list_verticals, query_compliance_position, get_case_study, scope_poc)
  • Stdio transport for local MCP clients (Claude Desktop, Continue.dev, etc.)
  • Open-source MIT release

Phase 2 (next)

  • HTTP+SSE transport for hosting at mcp.agrus.ai
  • Vercel deployment (matches the marketing-site stack)
  • Well-known manifest at /.well-known/mcp.json
  • Write tools with email-OTP verification:
    • request_quote — ballpark price band, no commitment
    • request_proposal — triggers formal proposal workflow + HubSpot lead with agrus_lead_source=agrus_mcp
    • book_consultation — Google Calendar handoff + HubSpot upsert + Slack alert
  • Rate limiting (Upstash Redis)
  • Submission to Anthropic MCP directory + awesome-mcp lists

Phase 3 (later)

  • Customer-scoped API-key authentication
  • check_engagement_status for existing-customer AI agents
  • npm package (@agrus/mcp-server)
  • Open-sourced HTTP transport layer as a reference implementation

Contributing

Issues and PRs welcome. The content modules (src/content/*.ts) are the easiest place to contribute — corrections, new compliance regimes, better case-study codenames. Larger changes (new tools, new transports) should open an issue first to discuss.

Related

License

MIT — see LICENSE. Copyright (c) 2026 Dappros Ltd.

来源:README.md,提交 e0ffe7f

工具

7

list_services

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.

输入参数vertical

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.

无需输入参数。

query_compliance_position

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.

输入参数regime必填use_case必填data_types

get_case_study

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.

输入参数slugvertical

scope_poc

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.

输入参数use_case必填vertical必填data_typestimeline_hinttarget_outcomescompliance_constraints

request_quote

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.

输入参数summary必填urgencyvertical必填compliance_constraints

request_proposal

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.

输入参数rolecompany必填urgencyvertical必填contact_name必填contact_email必填scope_summary必填persona_contextcompliance_constraints

版本历史

1
  1. v0.2.0最新Sep 16, 2026

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