SavantoAI MCP

Name: SavantoAI MCP
Author: SavantoAI

作者：SavantoAI版本 0.2.1i★ –i电脑或云端

注册名称io.github.SavantoAI/mcp-server

安装

概览

作者提供的说明（英文原文）

Manage your Savanto store from your AI: catalog, content, prompts, and analytics, by chat.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 电脑或云端
传输方式: stdio, Streamable HTTP
分类: 营销与社交媒体
你需要填写：SAVANTO_API_KEY

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：1 项中通过 1 项
在作者的服务器上运行：你向它提出的内容会经过他们的服务器。
需要你自己填写： SAVANTO_API_KEY

标为机密的值是你账户的钥匙。千万不要分享给别人，也不要粘贴到聊天里。

你需要

在云端运行无需安装任何东西，通过互联网连接
npm已安装 Node.js（用于 npx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude：

打开 Settings → Connectors
点击 Add custom connector
粘贴下面的地址，然后点击 Add
如果要求登录，请登录作者的服务

https://mcp.savanto.ai/mcp

或者在你的电脑上运行

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "savantoai": {
      "command": "npx",
      "args": [
        "-y",
        "@savantoai/mcp-server"
      ],
      "env": {
        "SAVANTO_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add --transport http savantoai https://mcp.savanto.ai/mcp

或者在你的电脑上运行

claude mcp add savantoai --env SAVANTO_API_KEY=your-value -- npx -y @savantoai/mcp-server

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "savantoai": {
      "url": "https://mcp.savanto.ai/mcp"
    }
  }
}

或者在你的电脑上运行

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "savantoai": {
      "command": "npx",
      "args": [
        "-y",
        "@savantoai/mcp-server"
      ],
      "env": {
        "SAVANTO_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "savantoai": {
      "type": "http",
      "url": "https://mcp.savanto.ai/mcp"
    }
  }
}

或者在你的电脑上运行

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "savantoai": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@savantoai/mcp-server"
      ],
      "env": {
        "SAVANTO_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

ChatGPT 只能连接互联网上的服务器：

打开网页版 ChatGPT → Settings → Connectors (Apps)
点击 Create 或 Add（部分套餐需要先在 Advanced 中开启 Developer mode）
粘贴下面的地址，起个名字，然后保存
如果要求登录，请登录作者的服务

https://mcp.savanto.ai/mcp

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上，无需账户。

需要你填写的值

SAVANTO_API_KEY 机密必填 env
A Savanto secret API key (if_sk_…) from your dashboard. Local/stdio use only; the hosted remote uses one-click OAuth instead.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

我们还没有读取这个服务器的工具列表；我们会轮流检查各个端点。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 SavantoAI 验证，该账户拥有此仓库
… 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
… 尚未检查
端点有响应
尚未检查；我们会轮流检查各个端点
… 尚未检查
使用 OAuth 登录
尚未检查；我们会轮流检查各个端点
… 尚未检查
工具描述中没有隐藏指令
尚未检查；我们会在检查端点时读取工具列表

与“营销与社交媒体”中的其他服务器比较i

星标数多于此分类中其他 2985 个服务器的 0%
发布到注册中心的时间比此分类中其他 2985 个服务器的 14% 更新
基础检查结果等于或优于此分类中其他 2985 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

SavantoAI MCP 安全吗？

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

你需要填写：SAVANTO_API_KEY

它在我的电脑上运行还是在云端？

两种方式都可以：安装在你的电脑上，或者连接云端版本。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（0.2.1）于5个月前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接，所以接受远程 MCP 服务器的应用也可以使用，例如开启开发者模式的 ChatGPT。

有什么可以替代它？

同一分类中有：MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

MCP YouTube Transcript

作者：jkawamoto

An MCP server retrieving transcripts of YouTube videos

在你的电脑上运行★ 495MIT10天前更新

安装

Google Analytics MCP

作者：surendranb

GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.

在你的电脑上运行★ 244MIT10天前更新

安装

BibiGPT YouTube Video Summarizer

作者：JimmyLv

AI video summarizer: summarize and transcribe YouTube, Bilibili, TikTok and podcast videos.

在云端运行★ 137MIT10天前更新

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

@savantoai/mcp-server

A local Model Context Protocol server that exposes your Savanto AI workspace to Claude, ChatGPT, Cursor, and any other MCP-compatible client — so you can configure, populate, and operate your store's AI assistant by talking to your own AI, instead of clicking through a dashboard.

What it does

Once configured, your agent gains a curated set of tools that mirror the Savanto REST API, spanning the full configure → observe → refine loop:

Category	Representative tools	Scope
Workspaces	`list_workspaces`, `create_workspace`, `update_workspace`, `delete_workspace`	`tenant:admin`
Configuration	`get_workspace_settings`, `update_workspace_settings`, custom-domain CRUD, `discover_tools`, `generate_domain_config`, `validate_custom_domain`, `test_domain_connection`, `generate_color_scheme`, chat/search widget config	`config:admin`
Content	`upsert_product`/`upsert_post` (+ `bulk_`, `list_`, `get_`, `patch_`, `delete_*`)	`admin:products`, `admin:posts`
Taxonomies	`upsert_taxonomy`, `bulk_upsert_taxonomies`, `list/get/delete_taxonomy`	`admin:taxonomies`
Prompts	`upsert_prompt`, `list_prompts`, `search_prompts`, `delete_prompt` (+ bulk)	`admin:prompts`, `prompts:read`
Webhooks	`create_webhook`, `list/get/update/delete_webhook`, `test_webhook`, `get_webhook_stats`	`admin:webhooks`
Crawl	`start_crawl`, `get_crawl_status`/`history`/`config`, `update_crawl_config`	`admin:posts`
Search	`search_products`, `search_posts`	`search:products`, `search:posts`
Analytics	`get_search_analytics`, `get_chat_analytics`, `get_feedback_analytics`, `search_search_logs`, `list_feedback`	`tenant:admin`, `feedback:admin`
Threads	`search_threads`, `get_thread`, `get_thread_messages`, `get_thread_analytics`, `delete_thread`, `bulk_delete_threads`	`threads:admin`
Chat	`chat`	`chat`
Diagnostics	`whoami`, `get_tenant_usage`	(none) / `tenant:admin`

Two things keep the surface safe and legible to clients:

Scope-gated at startup — the server probes /tenant/whoami and only registers tools your key can actually use. An agent is never shown a tool it would get a 403 for, and a publishable widget key sees almost nothing.
Annotated — every tool carries MCP hints (readOnlyHint, destructiveHint, idempotentHint) so clients can auto-approve safe reads and flag destructive writes; deletes additionally require an explicit confirm: true.

The server also exposes Skills (MCP prompts) — step-by-step playbooks for common multi-tool workflows:

onboard-store-end-to-end – create a workspace, ingest content, configure behaviour + branding, smoke-test
onboard-wordpress / onboard-shopify – platform-specific onboarding walkthroughs
configure-chat – tune persona, special instructions, and handoff rules
configure-custom-domain – wire a custom capability (order tracking, account lookup) to MCP servers / REST APIs
audit-and-improve – the observe→refine loop: find failing chats / zero-result searches / negative feedback and fix them
debug-empty-search – diagnose why a product search returns no hits
migrate-from-competitor – bulk-import from another chat vendor's export

Requirements

Node.js 20 or later
A secret Savanto API key (starts with if_sk_…). Create one in the API Keys page of your dashboard.

Publishable keys (if_pk_…) are client-side and cannot provision workspaces — the server will refuse to start with one.

Quick start

No global install needed — run it with npx:

export SAVANTO_API_KEY=if_sk_your_key_here

npx -y @savantoai/mcp-server

Point to a non-production cloud (staging, local dev):

export SAVANTO_API_URL=http://localhost:3001

Remote server (preview)

In addition to the local stdio server above, the same tool surface can run as a hosted HTTP server so clients connect to a URL instead of spawning npx — no local Node, no per-machine config. This is the path toward one-click "Connect to Claude/ChatGPT" (OAuth) onboarding; today it accepts your secret key as a Bearer token.

# Each client authenticates per-request — there is NO server-wide key.

SAVANTO_API_URL=https://api.savanto.ai PORT=8080 npx -y -p @savantoai/mcp-server savanto-mcp-http

The server mounts the MCP endpoint at /mcp and a liveness probe at /healthz. Clients send their key as Authorization: Bearer if_sk_…; the tool surface is scope-gated to that key's tenant, exactly as in the stdio server. Point an MCP client that supports remote (Streamable HTTP) servers at https://your-host/mcp with that bearer token.

Auth is currently the raw secret key. A future release replaces it with

OAuth-issued, tenant-scoped tokens so customers can connect with zero key

handling — the transport and tool layer are unchanged by that swap.

Client configuration

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

"mcpServers": { "savanto": { "command": "npx", "args": ["-y", "@savantoai/mcp-server"], "env": { "SAVANTO_API_KEY": "if_sk_your_key_here" } } } }

Restart Claude Desktop. You should see a hammer/tool icon in the message bar; the Savanto tools are listed there.

Cursor

In Cursor settings → Features → Model Context Protocol → Add new MCP server:

"savanto": { "command": "npx", "args": ["-y", "@savantoai/mcp-server"], "env": { "SAVANTO_API_KEY": "if_sk_your_key_here" } } }

Cline / Roo / other VS Code agents

Add to the extension's MCP config (usually a JSON file under ~/.cline or similar):

"mcpServers": { "savanto": { "command": "npx", "args": ["-y", "@savantoai/mcp-server"], "env": { "SAVANTO_API_KEY": "if_sk_your_key_here" } } } }

OpenAI Agents / Responses API

from openai import OpenAI

from mcp import StdioServerParameters

server = StdioServerParameters( command="npx", args=["-y", "@savantoai/mcp-server"], env={"SAVANTO_API_KEY": "if_sk_your_key_here"}, )

Local MCP Inspector (for debugging)

npx @modelcontextprotocol/inspector npx @savantoai/mcp-server

The Inspector gives you a web UI to list tools, call them directly, and watch request/response payloads — great for confirming your key is wired correctly before handing the server to an agent.

Example prompts

Once the server is registered in your MCP client, try:

"Set up a new Savanto workspace for acme-store, crawl https://acme.test, give it an outdoor-adventure tone, and brand the widget around #0a7d2c." *(end-to-end onboarding)*

"Look at acme-store's last 30 days — what are visitors searching for that returns nothing, and which conversations went unresolved? Then add content to fix the top few." *(the observe→refine loop)*

"Add an order-tracking capability to acme-store backed by our MCP server at https://mcp.acme.test/orders, validate it, and test it before enabling." *(custom domain)*

"Why did this conversation get a thumbs-down?" — pull list_feedback, read the thread, and propose a fix.

The agent picks the right tools automatically (and clients can auto-approve the read-only ones). You can also invoke a Skill explicitly — e.g. in Claude Desktop, /onboard-store-end-to-end or /audit-and-improve kicks off that full playbook.

Environment variables

Variable	Default	Purpose
`SAVANTO_API_KEY`	_(required)_	Your secret API key (`if_sk_…`).
`SAVANTO_API_URL`	`https://api.savanto.ai`	Override for staging / local dev.

Security

Always use separate API keys per agent / machine — so you can revoke one without affecting the others. The API Keys page tracks the last-used timestamp of each key.
Keys are passed via environment variables, never logged. The server prints a one-line identity banner on startup (to stderr) showing the tenant id and scope list — no secrets.
The server runs over stdio and never opens a network port. It only speaks to the Savanto API host you point it at.
delete_workspace requires an explicit confirm: true parameter in the tool call — a safety gate against hallucinated destructive operations.

Local development

From the repo root:

npm install

npm run build --workspace=@savantoai/mcp-server SAVANTO_API_KEY=if_sk_… SAVANTO_API_URL=http://localhost:3001 node sdks/mcp/dist/stdio.js

Run the tests:

npm run test --workspace=@savantoai/mcp-server

License

MIT. See LICENSE.

SavantoAI MCP

概览

PopNx MCP 的三大支柱

它能帮你做什么

安装

安装之前

或者在你的电脑上运行

或者在你的电脑上运行

或者在你的电脑上运行

或者在你的电脑上运行

需要你填写的值

它能做什么

基础检查i

作者与仓库一致

仍在维护

有许可证

端点有响应

使用 OAuth 登录

工具描述中没有隐藏指令

与“营销与社交媒体”中的其他服务器比较i

常见问题

替代选择

MCP YouTube Transcript

Google Analytics MCP

BibiGPT YouTube Video Summarizer

作者的 README

@savantoai/mcp-server

What it does

Requirements

Quick start

Remote server (preview)

Client configuration

Claude Desktop

Cursor

Cline / Roo / other VS Code agents

OpenAI Agents / Responses API

Local MCP Inspector (for debugging)

Example prompts

Environment variables

Security

Local development

License