growth-engineer README

The project's README from github.com/GetBrew/growth-engineer. As one markdown file: README.md.

The growth.engineer home page, with the card that connects Claude to the MCP server

growth.engineer

Go-to-market tools and workflows, written as files any agent can run.

An open-source catalog of go-to-market companies, the functions an agent can call on each one, and workflows that chain those functions into a result. Every entry is a markdown file in this repository.

growth.engineer  ·  Connect your agent  ·  Contribute  ·  Develop

Live site CI MCP server with a read-only catalog Built with Next.js License: MIT GitHub stars


What is this?

Handing a go-to-market tool to an agent means digging through docs written for people: which key to create, which endpoint to call, whether there is an MCP server, what a call costs. And a growth play that works usually lives in someone's notes, where no agent can run it.

growth.engineer writes both down as markdown files an agent can follow:

Entry Example key What the file holds
Company apollo Who the company is and how an agent reaches it: MCP server, CLI or API, and the credential each one needs.
Tool apollo/enrich-person One function an agent can call: the exact MCP tool, CLI command or API endpoint, and the docs page that names it.
Workflow funding-signal-outbound Up to ten steps across tools that reach a result: the one motion it serves, the outcome the user gets, the inputs to ask for, how to set up each tool, and the steps.

Paste a workflow file into Claude, ChatGPT, Cursor or any other agent and it can run the play. The file tells the agent to ask before it sends a message, spends money or changes data.

Facts come from each vendor's own documentation, and every tool links the page that documents its call.


Connect your agent

The site runs an MCP server at https://www.growth.engineer/mcp (Streamable HTTP, no sign-in). Its search tool finds workflows, tools and companies, and get returns a file; neither changes anything. A third tool, submit_feedback, sends a bug report, request or question to the maintainers. Every workflow is also an MCP prompt that takes the workflow's inputs as arguments, and three more prompts (contribute-workflow, contribute-tool, contribute-company) walk an agent through adding to the catalog.

Client How to add it
Claude Settings → Connectors → Add custom connector, then paste the URL.
Claude Code claude mcp add --transport http growth-engineer https://www.growth.engineer/mcp
ChatGPT Settings → Apps & Connectors → Advanced settings, turn on Developer mode, then Create. Paste the URL and pick No authentication.
Codex In ~/.codex/config.toml, add a [mcp_servers.growth-engineer] table with url = "https://www.growth.engineer/mcp".
Cursor In mcp.json, add "growth-engineer": { "url": "https://www.growth.engineer/mcp" } under mcpServers.

Or fetch the files

Every file is public. There is no key and no sign-in.

URL Returns
/workflows/<name>.md A workflow, ready to paste into an agent
/tools/<company>/<name>.md One tool
/companies/<handle>.md A company and its tools
/tags/<namespace>/<slug>.md Everything with a tag, such as /tags/capability/enrich-contacts.md
/llms.txt The catalog's definitions and an index of every file
/llms-full.txt Every company, tool and workflow file in one document
/sitemap.xml Every page, with the date it last changed

A company, tool or workflow page also returns its file to a request with Accept: text/markdown.

# A workflow file
curl https://www.growth.engineer/workflows/funding-signal-outbound.md

# The same file, by content negotiation
curl -H 'Accept: text/markdown' https://www.growth.engineer/workflows/funding-signal-outbound

Contribute

The catalog lives in this repository, and every addition or fix is a pull request.

To Add or edit Field reference Agent skill
Share a workflow workflows/<name>.md workflows/README.md add-workflow
Add a company and its tools companies/<handle>/company.md and tools/<name>.md companies/README.md research-company
Fix a fact The file that states it The same READMEs

Check your work before you open the pull request. CI runs the same check.

pnpm content:check   # every problem in the catalog, each with its file

CONTRIBUTING.md covers the few rules worth knowing first.


How it works

There is no backend and no database. At build time, a compiler in lib/content/ reads every file, validates it against a strict schema and resolves every reference. One renderer turns each company, tool and workflow into the file agents fetch, and Next.js prerenders every page from the same data. Deploying the site publishes the catalog.

companies/  workflows/  tags.yml
        │
        ▼
lib/content/                     read, validate, resolve, derive
        │
        ▼
lib/catalog/render-markdown.ts   one renderer, golden-tested
        │
        ├─▶ pages, prerendered at build
        ├─▶ .md files, /llms.txt, /llms-full.txt
        └─▶ /mcp, the MCP server

The one runtime store is optional: an Upstash Redis that counts how often each workflow is copied, for its "Uses" and the Hot and Popular lists. Without it, the counts are hidden.

Visits are measured with Vercel Web Analytics and Speed Insights, and AI crawlers and AI-referred visits with Notra. See docs/setup.md.


Project layout

growth-engineer/
├─ companies/<handle>/    company.md and tools/<name>.md (logos live on the CDN)
├─ workflows/<name>.md    one file per workflow
├─ tags.yml               the tag vocabulary
├─ app/                   Next.js routes: pages, .md files, /mcp, llms.txt, sitemap
├─ components/            layout, catalog lists, detail pages, UI primitives
├─ lib/
│  ├─ content/            the build-time compiler
│  ├─ catalog/            keys, the markdown renderer, search, loaders
│  ├─ mcp/                the MCP server's tools and prompts
│  ├─ seo/                metadata, structured data, llms.txt
│  └─ usage/              the optional copy counter
├─ tests/                 Vitest: golden files, the content suite, schema checks
├─ docs/                  architecture, data model, file format, setup
└─ .agents/skills/        add-workflow, research-company

Local development

Prerequisites: Node 22+ and pnpm 11 (corepack enable installs the pinned version).

pnpm install
pnpm dev             # http://localhost:3000

Edits to companies/, workflows/ and tags.yml show on the next refresh. Add .md to a company, tool or workflow URL to see the file an agent gets.

Nothing needs configuring. .env.example lists the optional variables:

Variable Used for
NEXT_PUBLIC_SITE_URL The origin printed in /llms.txt and page metadata. On Vercel it defaults to the deployment's hostname.
KV_REST_API_URL, KV_REST_API_TOKEN, KV_REST_API_READ_ONLY_TOKEN The copy counter. Without them, the counts are hidden.
GITHUB_TOKEN The star count in the header. Without it, GitHub allows 60 unauthenticated requests an hour.
NOTRA_GEO_TOKEN AI-traffic analytics: the proxy reports AI crawlers and AI-referred visits to Notra. Without it, nothing is sent.

Scripts

Script Does
pnpm dev Starts the dev server
pnpm content:check Parses, validates and renders the whole catalog
pnpm check Biome and a fast typecheck
pnpm test:run The unit suite, including the content checks
pnpm tsc / pnpm lint The full typecheck and lint
pnpm build Production build
pnpm validate Lint, typecheck and tests together
pnpm hygiene Docs links, the content tree, unused code, duplicate dependencies

Heavy commands wait their turn behind a lock, so several worktrees can run checks without running out of memory. See docs/maintainers/validation.md.


Deploy

The site runs on Vercel with the settings in vercel.json. Every page and file is generated at build time, so merging to main publishes the catalog. docs/setup.md has the details.


Docs


License

MIT © Brew

growth-engineer (GetBrew/growth-engineer)

Searching Database…

这是什么?growth.engineer —— 一个开源的 go-to-market 工具与打法目录,全部以 markdown 文件编写,任何 AI 智能体都能直接执行:包括公司信息、每个公司可调用的功能,以及把这些功能串成成果的工作流。
它是一个可以浏览的网站,还是一堆给智能体用的文件?两者都是。这个目录以纯 .md 文件的形式存放在仓库里,同时发布为一个 Next.js 网站,上面还架了一个只读的 MCP 服务器;在任何页面 URL 后面加上 .md,就能拿到智能体看到的那份原始文件。
怎么把我的 AI 智能体接到它上面?把你的智能体指向该网站的 MCP 服务器:在 Claude Code 里运行 claude mcp add --transport http growth-engineer;在 Claude、ChatGPT、Codex 和 Cursor 中,则在连接器设置里粘贴同一个 URL。不需要密钥,也不需要登录。
智能体会不会自作主张给人发邮件或花钱?它会让你全程知情:每个工作流都要求智能体在发送消息、花钱或改动数据之前先征求你的同意,而且 MCP 服务器是只读的 —— 只有搜索、获取和一个反馈工具,没有别的。
这些增长打法为什么要写成 markdown 文件?厂商文档是写给人看的 —— 密钥、接口地址、费用 —— 而真正可用的打法通常躺在智能体无法执行的笔记里。写成文件后,智能体就能直接照着步骤执行,整个目录还有 /llms.txt 做索引。
这个 MCP 服务器能做什么?它是只读的:search 用于查找工作流、工具和公司,get 用于返回一个文件,submitFeedback 用于给维护者留言。每个工作流同时也是一个 MCP prompt,把工作流的输入作为参数传入。
这些要花钱吗?目录本身免费,采用 MIT 许可证。但工作流所串联的 GTM 工具(比如 Apollo)按它们自己的套餐收费 —— 这正是工作流要求智能体在花钱之前先询问你的原因。
Creator
GetBrew
Size
49.5 MB
Stars
249
Updated
CommitOct 16
Age
1mo
Commits · 90 Days