Tool Discovery Playbook

工具如何被发现和调用 How Tools Get Discovered & Called

▸ 全局总览 — 点击卡片跳转详细手册 ▸ Overview — click cards to jump to details
流量 ↓ Traffic ↓
用户和 AI 代理通过各渠道发现你Users & AI agents find you via channels above
Your Website
navigator.modelContext.registerTool({ ... })
你的网站声明「我能做什么」Your site declares "what I can do"
↓ 调用 ↓ Calls
AI 代理识别工具并自动调用AI agents detect tools & invoke them
Claude Chrome Extension
浏览器扩展捕获 registerTool Browser ext captures registerTool
Chrome Native
实验阶段 · 原生集成 Experimental · native integration
Local Relay
Claude Desktop · Cursor · VS Code Claude Desktop · Cursor · VS Code

核心战术 Core Tactics
TACTIC 01
关键词策略:按意图分层 Keyword Strategy: Layer by Intent
不要只抢高竞争大词,按搜索意图分层布局:

信息型「什么是 MCP 工具」— 写博客建权威,排名慢但积累品牌
对比型「X vs Y 哪个好」— 做对比页,截获决策阶段用户,转化最高
品牌型「你的工具名 + 教程」— 提前布局,防竞品截流

长尾词(3-5 词的具体问题)竞争低、意图精准、转化高,优先起步。
Don't just chase high-competition keywords. Layer by search intent:

Informational "what is MCP tool" — blog posts build authority slowly
Comparison "X vs Y" — comparison pages capture decision-stage users, highest conversion
Branded "your tool name + tutorial" — claim early, prevent competitors from hijacking

Start with long-tail keywords (3-5 word specific queries) — low competition, precise intent, high conversion.
SEO
TACTIC 02
技术博客 = 最强 SEO 资产 Technical Blog = Your Strongest SEO Asset
每篇文章解决一个具体问题,结尾自然引出工具。

选题公式:「How to [解决用户痛点] using [你的工具]」
例:「How to expose your SaaS tools to Claude in 5 minutes」

内容结构:痛点描述 → 解决方案 → 代码示例 → 工具链接
发布渠道:自己博客(权重归你)+ dev.to + Medium(额外曝光)
Each article solves one specific problem. Naturally introduce your tool at the end.

Topic formula: "How to [solve user pain] using [your tool]"
e.g.: "How to expose your SaaS tools to Claude in 5 minutes"

Content structure: Pain → Solution → Code example → Tool link
Channels: Your blog (owns the SEO weight) + dev.to + Medium (extra exposure)
内容营销Content
TACTIC 03
工具目录提交(不可跳过) Directory Submission (Don't Skip)
Product Hunt — 发布日冲榜可获数千访问,提前 2 周预热
GitHub Awesome 列表 — awesome-mcp-servers、awesome-ai-tools,提 PR
npm / PyPI — 包名即 SEO,开发者直接搜到
AlternativeTo — 截获竞品用户搜索流量
There's an AI for That — AI 工具聚合平台,收录 45000+ 工具
Toolify.ai / Futurepedia — 补充覆盖
Product Hunt — Launch day can bring thousands of visits, warm up 2 weeks early
GitHub Awesome lists — awesome-mcp-servers, awesome-ai-tools, submit PRs
npm / PyPI — Package name is SEO, devs search directly
AlternativeTo — Capture competitor search traffic
There's an AI for That — AI tool aggregator, 45,000+ tools listed
Toolify.ai / Futurepedia — Additional coverage
目录Directories
TACTIC 04
社区运营:先给后取 Community: Give Before You Take
在 HackerNews、Reddit、Discord AI 社群先回答别人问题,建立信任。

当你分享工具时,社区会接受而非反感。

Show HN 格式:「Show HN: [工具名] – [一句话功能]」
一条好的 Show HN 可带来数千精准开发者访问。
Answer questions first in HackerNews, Reddit, Discord AI communities. Build trust.

When you share your tool, the community will welcome rather than resist it.

Show HN format: "Show HN: [Tool] – [One-line description]"
A good Show HN can bring thousands of targeted developer visits.
社区Community
执行清单 Action Checklist
SEO & 目录 · 行动清单 SEO & Directories · Action Items
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各平台打法 Platform-Specific Tactics
平台Platform
核心打法Core Tactic
适合什么Best For
Twitter / X
60s Demo GIF/视频 + 第一句话就是结果 + 正文放链接 60s demo GIF/video + lead with result + link in body text
开发者/技术圈扩散,最强 Dev 流量 Dev community spread, strongest dev traffic
小红书Xiaohongshu
首图必须是结果截图,口语化心得,回复每条评论 Lead image must be the result screenshot, casual tone, reply to every comment
中文用户种草转化,效率工具类表现好 Chinese market, productivity tools perform well
YouTube / B 站
标题含工具名 + 场景词,描述框第一行放链接 Title includes tool name + scenario, first line of description is the link
长效搜索流量,教程类 5-15 分钟最佳 Long-term search traffic, tutorials 5-15 min work best
TikTok / 抖音Douyin
纯结果展示,不解释原理,加文字说明(静音场景) Pure result showcase, no explanations, add text overlays (silent viewing)
大众用户,爆发性强,转化需配合 bio 链接 Mass audience, explosive reach, conversion needs bio link
Newsletter
直接邮件作者,一句话介绍 + Demo 链接 Email the author directly, one-line intro + demo link
精准高质量用户,读者已经对该领域感兴趣 Precise high-quality users, readers already interested in the space
高转化 Demo 视频公式 High-Conversion Demo Video Formula
视频结构模板 Video Structure Template
0-3s 直接展示最惊艳的结果画面(不要开场 logo)
3-8s 「只需要 X 步 / X 秒」建立惊喜感
8-30s 实时演示核心操作(不剪辑,保真实感)
30-45s 展示第二个使用场景,拓展想象空间
结尾 明确 CTA:「链接在 bio / 评论置顶」
0-3s Show the most impressive result immediately (no intro logo)
3-8s "Just X steps / X seconds" — build the wow factor
8-30s Live demo of core workflow (no cuts, keep it real)
30-45s Show a second use case, expand imagination
End Clear CTA: "Link in bio / pinned comment"
全程加字幕(大量用户静音观看)· 发布后 1 小时内回复前 10 条评论 Always add subtitles (many users watch muted) · Reply to first 10 comments within 1 hour of posting
执行清单 Action Checklist
短视频 & 社交 · 行动清单 Video & Social · Action Items
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原理:LLM 怎么「知道」推荐你? How LLMs "Know" to Recommend You
两个来源 Two Sources
① 训练数据 — 博客 / GitHub / Stack Overflow 中提到你的内容 → 权重积累 → LLM 主动推荐
② 实时检索 — Perplexity / ChatGPT Search 实时抓取 → 页面结构清晰 + 权威性高 → 被引用
① Training data — Blog / GitHub / Stack Overflow content mentioning you → weight accumulation → LLM recommends proactively
② Real-time retrieval — Perplexity / ChatGPT Search crawls in real time → clear page structure + high authority → gets cited
核心原则:让 AI 一眼看懂你是什么、解决什么问题、什么时候用你 Core principle: Let AI instantly understand what you are, what you solve, when to use you
核心战术 Core Tactics
TACTIC 01
写给 AI 看的页面内容 Write Page Content for AI
首页加一句话定义:
「[工具名] 是 [类别] 工具,帮助 [用户] 解决 [问题]」

文档加 FAQ 页面,用 Q&A 格式,问题要和用户真正会问 AI 的一致。
FAQ 格式的 Q&A 内容更容易被 AI 搜索直接引用——结构化的问答更匹配用户提问方式
Add a one-line definition to your homepage:
"[Tool] is a [category] tool that helps [users] solve [problem]"

Add an FAQ page to your docs using Q&A format. Questions should match what users actually ask AI.
FAQ-style Q&A content is more likely to be cited by AI search — structured Q&A matches how users ask questions
AIO
TACTIC 02
在 AI 训练数据源布点 Place Markers in AI Training Sources
GitHub README — 结构化 + 徽章 + 截图 + 快速上手代码,LLM 训练数据的高权重来源
dev.to / Medium — 被 LLM 训练数据广泛收录
Stack Overflow — 在相关问题下给出包含你工具的解决方案
HN Show HN — 被几乎所有主流 LLM 数据集收录
GitHub README — Structured + badges + screenshots + quickstart code, high-weight LLM training source
dev.to / Medium — Widely included in LLM training data
Stack Overflow — Post solutions that include your tool on relevant questions
HN Show HN — Included in nearly all major LLM datasets
训练数据Training Data
自测:AI 可见度检查(每月一次) Self-Test: AI Visibility Check (Monthly)
AI 可见度 · 行动清单 AI Visibility · Action Items
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第一步:在网页注册工具(通用基础) Step 1: Register Tools on Your Page (Foundation)
// Register your tool on the web page — shared foundation for all 3 channels if ('modelContext' in navigator) { navigator.modelContext.registerTool({ name: 'search_products', // description is how AI decides WHEN to call you // Formula: [what it does] + Use this when [trigger] + Returns [output] description: `Search the product catalog. Use this when the user wants to find products, check availability, or compare items. Returns product name, price, and stock status.`, parameters: { type: 'object', properties: { query: { type: 'string', description: 'Natural language search query', examples: ['red shoes', 'wireless headphones under $100'] }, limit: { type: 'number', default: 10 } }, required: ['query'] }, handler: async ({ query, limit = 10 }) => { const data = await fetchProducts(query, limit); return { products: data, total: data.length }; } }); }
三种接入通道对比 Three Integration Channels Compared
通道Channel
接入方式How It Works
适用场景Best For
Claude Chrome Extension
浏览器扩展注入,捕获 registerTool 声明,暴露给浏览器内 AI agents Browser extension injects, captures registerTool declarations, exposes to in-browser AI agents
用户安装扩展后即可使用,成熟可用 Works once user installs the extension, production-ready
Chrome Native
浏览器原生读取页面工具声明,无需扩展 Browser natively reads page tool declarations, no extension needed
实验阶段,最低摩擦接入路径 Experimental, lowest-friction integration path
Local Relay
本地中继服务,将网页工具桥接给 Claude Desktop / Cursor / VS Code Local relay bridges web page tools to Claude Desktop / Cursor / VS Code
桌面 AI 用户,成熟可用 Desktop AI users, production-ready
description 写法:决定 AI 何时调用你 Writing description: Determines When AI Calls You
✖ 糟糕的 description ✖ Bad description
"A tool for searching products"

只说功能,没说何时用。
AI 不知道在什么意图下调用你,大概率不会触发
Only describes function, not when to use it.
AI doesn't know which user intent triggers it, likely won't fire.
✔ 好的 description ✔ Good description
"...Use this when the user wants to find products or check availability. Returns name, price, stock."

说了触发条件 + 返回内容。
AI 精准知道何时调用你。
States trigger condition + return content.
AI precisely knows when to call you.
执行清单 Action Checklist
Agent 接入 · 行动清单 Agent Integration · Action Items
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llms.txt — AI 爬虫的工具声明文件 llms.txt — Tool Declaration for AI Crawlers
# /llms.txt — Markdown format, place in site root # Spec: https://llmstxt.org # MyTool > A one-line description of what your tool does, > written for LLMs to understand your use case. ## Docs - [API Reference](https://yoursite.com/docs) - [OpenAPI Spec](https://yoursite.com/openapi.json) ## Usage Use this tool when users need to [trigger scenario]. Returns [output description]. ## Integration - Supports MCP server registration - Provides OpenAPI 3.x schema
核心战术 Core Tactics
TACTIC 01
提交 AI 工具专属目录 Submit to AI Tool Directories
与传统工具目录不同,这些目录直接被 AI 系统引用:

MCP Registry — MCP 开源社区维护,Anthropic / GitHub / Microsoft 共建
Smithery.ai — 最大的 MCP 服务器市场,支持搜索和部署
Glama.ai — AI 工作台 + MCP 服务器目录
OpenTools.ai — AI 工具发现目录,社区评分排序

提交后保持更新,过时信息会降低信任度。
Unlike traditional directories, these are directly referenced by AI systems:

MCP Registry — MCP open-source community, backed by Anthropic / GitHub / Microsoft
Smithery.ai — Largest MCP server marketplace, search & deploy
Glama.ai — AI workspace + MCP server directory
OpenTools.ai — AI tool discovery directory, community-ranked

Keep listings updated; stale info reduces trust.
AI 目录AI Directories
TACTIC 02
OpenAPI / JSON Schema 规范化 OpenAPI / JSON Schema Standardization
提供完整的 openapi.json,让 AI 系统自动理解你的所有工具:

· 每个 endpoint 加 summary 和 description
· 所有参数加 description + example
· 返回值加完整 schema 定义

规范的 schema 让 AI 零摩擦调用,可显著降低调用错误率 (基于 OpenAPI 规范使用的行业经验值)
Provide a complete openapi.json so AI systems can understand all your tools:

· Add summary and description to every endpoint
· Add description + example to all parameters
· Full schema definition for return values

Well-defined schemas enable zero-friction AI calls, significantly reducing error rates (industry experience with OpenAPI adoption)
API
TACTIC 03
追踪 AI 来源流量 Track AI-Source Traffic
在 referrer 或 User-Agent 中识别 AI agent 来源:

Perplexity 引用:referrer 包含 perplexity.ai
AI agent 调用:User-Agent 包含 claude / openai / copilot
MCP 调用:加自定义 header X-Source: mcp

建立独立的 AI 流量看板,和传统流量分开分析。
Identify AI agent sources in referrer or User-Agent:

Perplexity citations: referrer contains perplexity.ai
AI agent calls: User-Agent contains claude / openai / copilot
MCP calls: add custom header X-Source: mcp

Build a separate AI traffic dashboard, analyze independently from traditional traffic.
追踪Tracking
TACTIC 04
稳定性 = 可发现性 Stability = Discoverability
工具不稳定会导致 AI agent 调用失败,用户不再使用:

· 版本控制:提供 changelog,旧版本保持兼容
· 错误处理:返回清晰的错误信息,AI 可以理解
· 响应时间:尽量 < 500ms,AI agent 有超时机制
· 状态页面:提供 /status 接口,AI 检查可用性
Unstable tools cause AI agent call failures, users stop using them:

· Versioning: Provide changelog, keep old versions compatible
· Error handling: Clear error messages AI can understand
· Response time: Target < 500ms, AI agents have timeout limits
· Status page: Provide /status endpoint, AI checks availability
可靠性Reliability
执行清单 Action Checklist
系统优化 · 行动清单 System Optimization · Action Items
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核心战术 Core Tactics
TACTIC 01
GitHub 冷启动:用贡献换关系 GitHub Cold Start: Trade Contributions for Connections
没有人脉的时候,代码就是你的名片:

· 找到你工具所在领域的热门开源项目
· 不要提 typo fix,要提真正解决问题的 PR——修 bug、加测试、补文档
· 在 Issue 里给出有深度的分析,maintainer 会记住你
· 持续贡献 3-5 次后,你自然成为"圈内人"

关键:你帮别人解决了问题,别人才会关心你在做什么。
When you have no network, code is your business card:

· Find popular open-source projects in your tool's domain
· Don't submit typo fixes — submit PRs that solve real problems: fix bugs, add tests, improve docs
· Give thoughtful analysis in Issues — maintainers remember contributors
· After 3-5 meaningful contributions, you naturally become an "insider"

Key: help others solve problems first, then they'll care about what you're building.
GitHub
TACTIC 02
进入 Awesome List Get Into Awesome Lists
Awesome Lists 是开发者找工具的入口,一次收录 = 长期曝光:

· 搜索 awesome-{你的领域},研究已收录项目的共同点
· 提交 PR 时写清楚:一句话说明 + 和已有工具的区别
· README 要规范:清晰的 Install / Quick Start / API 文档
· 如果被拒,看 maintainer 的反馈改进后重新提交

很多 Awesome List 有上万 star,被收录后你的项目会持续获得点击。
Awesome Lists are where devs discover tools — one listing = long-term exposure:

· Search awesome-{your-domain}, study what listed projects have in common
· PR description: one-line summary + how you differ from existing tools
· README must be polished: clear Install / Quick Start / API docs
· If rejected, read maintainer feedback, improve, and resubmit

Many Awesome Lists have 10k+ stars — getting listed means sustained traffic to your project.
Awesome List
TACTIC 03
Show HN / Reddit 首帖 Show HN / Reddit First Post
标题决定生死,讲你解决了什么问题,不是你做了什么产品:

· Show HN:标题格式 "Show HN: [工具名] – [解决什么问题]"
· 主动回复每一条评论——作者的参与度直接影响社区好感和 upvote
· r/SideProjectr/webdevr/selfhosted:找到你工具对应的 subreddit
· 发帖时间:美国西海岸上午 9-11 点(UTC-8)流量最高

一篇好的 Show HN 帖子可以带来几千次访问和持续的 backlink。
Title makes or breaks it — describe the problem you solve, not the product you built:

· Show HN: title format "Show HN: [Tool] – [Problem it solves]"
· Reply to every comment — author engagement drives community goodwill and upvotes
· r/SideProject, r/webdev, r/selfhosted: find the subreddit for your tool's niche
· Post timing: 9-11 AM US West Coast (UTC-8) gets highest traffic

A good Show HN post can drive thousands of visits and lasting backlinks.
社区首发Launch Post
TACTIC 04
Discord / Slack 社区潜入 Discord / Slack Community Infiltration
进社区第一天就发链接 = 被踢。正确的节奏:

第 1-2 周:只回答别人的问题,不提自己的工具
第 3 周:有人问到相关问题时,自然地说"我刚好做了个工具解决这个"
之后:你已经有了信任基础,分享自己的更新不会被反感

重点社区:
· 你所在框架/语言的官方 Discord
· Indie Hackers 社区
· 目标用户群体聚集的垂直社区
Dropping links on day one = getting kicked. The right rhythm:

Week 1-2: Only answer others' questions, don't mention your tool
Week 3: When someone asks a relevant question, naturally say "I built something for this"
After: You've built trust — sharing updates won't feel spammy

Key communities:
· Official Discord of your framework/language
· Indie Hackers community
· Niche communities where your target users gather
社区渗透Community
TACTIC 05
找到"连接者"——从提供价值开始 Find "Connectors" — Start by Giving Value
每个技术圈子都有几个关键人物:newsletter 作者、YouTube 博主、Twitter KOL。
素人不能直接求推广,要从提供价值开始:

· 给他们的文章/视频写有深度的评论或补充
· 帮他们翻译内容、纠正技术错误、提供数据
· 在 Twitter 上持续转发 + 加有价值的评论(不是"太棒了")
· 关系建立后,发一条简短 DM:"我做了个工具,想听你的看法"

一个 KOL 的真诚推荐 > 100 次自我推广。但前提是你先帮了他。
Every tech circle has key figures: newsletter authors, YouTubers, Twitter influencers.
As a nobody, don't ask for promotion directly — start by giving value:

· Write insightful comments or additions on their articles/videos
· Translate their content, fix technical errors, provide data
· Retweet with valuable commentary on Twitter (not just "great post!")
· After building rapport, send a short DM: "I built a tool, would love your take"

One genuine recommendation from a KOL > 100 self-promotions. But you have to help them first.
关系建立Networking
TACTIC 06
Build in Public:让别人主动来找你 Build in Public: Let Others Come to You
前 5 条都是你主动出击,这条反过来——让别人来关注你:

· 在 Twitter/X 上持续分享构建过程:遇到了什么问题、怎么解决的、学到了什么
· 分享真实数据:用户数、收入、失败的尝试——真实感比包装更吸引人
· 固定格式如 "Day 14: ..." 或 "本周进展",让人养成追更习惯
· 关键:分享过程和思考,不是反复推销产品链接

Build in Public 的好处是双向的——你吸引到的关注者天然就是潜在用户和传播者。
The first 5 tactics are outbound — this one flips it and brings people to you:

· Share your building process on Twitter/X: problems you hit, how you solved them, what you learned
· Share real numbers: user count, revenue, failed experiments — authenticity beats polish
· Use a consistent format like "Day 14: ..." or "This week's progress" so people follow along
· Key: share process and thinking, not repeated product links

Build in Public works both ways — the followers you attract are naturally potential users and amplifiers.
Build in Public
执行清单 Action Checklist
社区 & 开发者关系 · 行动清单 Community & DevRel · Action Items
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