PostHog MCP Server
Official PostHog MCP Server for product analytics, feature flags, experiments, and more.
Schedule, publish, and review social posts and analytics for a Markaestro brand.
选择你使用的 AI 应用,然后复制设置。
通过 5/5 项检查 · 你的提问会经过开发者的服务器(markaestro.com)
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude · 约 2 分钟
不需要密钥,不用安装程序 · 在 claude.ai 或桌面应用设置一次,即可在聊天中使用 · 免费账户可添加 1 个 · Team/Enterprise 方案由所有者(Owner)添加
CustomizeConnectors
把这里的内容复制到 Claude 中同名的输入框,然后点击 Continue
Markaestrohttps://markaestro.com/api/public/v1/mcpAuthentication 保持 Claude 检测到的设置,然后点击 Add
+ConnectorsMarkaestro
用 Markaestro 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 Markaestro,或回答中出现 Markaestro 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
仅企业版 ChatGPT 可连接
适用于网页版 ChatGPT Business、Enterprise 或 Edu,需由工作区管理员或所有者添加 · 使用 Free、Plus 或 Pro:你的 ChatGPT 方案暂时无法自行连接 MCP
Plugins+Add custom MCP server
输入名称,在 Connection 下粘贴地址,勾选风险提示,然后点击 Create as a plugin
Markaestrohttps://markaestro.com/api/public/v1/mcp开启新聊天,输入前先从插件列表中选择 Markaestro
用 Markaestro 告诉我你能帮我做什么,然后做一件给我看✓ 如果 ChatGPT 说正在使用 Markaestro,或回答中出现 Markaestro 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 OpenAI 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Claude Code · 约 2 分钟
不需要密钥,不用安装程序
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
claude mcp add --transport http --scope user markaestro https://markaestro.com/api/public/v1/mcp应能看到 Markaestro 在列表中并显示已连接
用 Markaestro 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude Code 说正在使用 Markaestro,或回答中出现 Markaestro 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Cursor · 约 2 分钟
不需要密钥,不用安装程序
用 Markaestro 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Cursor 说正在使用 Markaestro,或回答中出现 Markaestro 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同
可连接 VS Code · 约 2 分钟
不需要密钥,不用安装程序
用 Markaestro 告诉我你能帮我做什么,然后做一件给我看✓ 如果 VS Code 说正在使用 Markaestro,或回答中出现 Markaestro 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同
其他支持 MCP 的应用(如 Windsurf、Zed、Gemini CLI)添加方式各不相同,请在应用列表中查看
通过网页连接的应用使用的地址
https://markaestro.com/api/public/v1/mcpJSON 设置在下方“开发者专用”中
Claude Code
claude mcp add --transport http --scope user markaestro https://markaestro.com/api/public/v1/mcpCursor (~/.cursor/mcp.json)
{
"mcpServers": {
"markaestro": {
"url": "https://markaestro.com/api/public/v1/mcp"
}
}
}VS Code (mcp.json)
{
"servers": {
"markaestro": {
"type": "http",
"url": "https://markaestro.com/api/public/v1/mcp"
}
}
}Claude Code
claude mcp add --scope user markaestro --env MARKAESTRO_API_KEY=your-value --env MARKAESTRO_READ_ONLY=your-value -- npx -y @markaestro/mcpClaude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"markaestro": {
"command": "npx",
"args": [
"-y",
"@markaestro/mcp"
],
"env": {
"MARKAESTRO_API_KEY": "your-value",
"MARKAESTRO_READ_ONLY": "your-value"
}
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"markaestro": {
"command": "npx",
"args": [
"-y",
"@markaestro/mcp"
],
"env": {
"MARKAESTRO_API_KEY": "your-value",
"MARKAESTRO_READ_ONLY": "your-value"
}
}
}
}VS Code (mcp.json)
{
"servers": {
"markaestro": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@markaestro/mcp"
],
"env": {
"MARKAESTRO_API_KEY": "your-value",
"MARKAESTRO_READ_ONLY": "your-value"
}
}
}
}MARKAESTRO_API_KEY 机密 必填 envMARKAESTRO_READ_ONLY env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。
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
通过互联网连接,适用于
ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast
在你的电脑上运行,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
服务器要求先登录,才会列出它的工具。
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12日
注册名称已通过域名 markaestro.com 验证(注册中心会核实域名所有权)
代码最后更新于8天前
使用 MIT
在 226 毫秒内响应(HTTP 401)
声明支持 OAuth 登录,你的 AI 应用可以带你去登录
尚未检查;我们会在检查端点时读取工具列表
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
还没有评价
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。
它在 5 项适用的基础检查中通过了 5 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。
你需要填写:MARKAESTRO_API_KEY
两种方式都可以:安装在你的电脑上,或者连接云端版本。
GitHub 仓库最后更新于8天前,最新版本(0.4.0)于8天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,因此也能用于支持远程 MCP 的应用,例如 ChatGPT Business 及以上方案。
同一分类中有:PostHog MCP Server, Openshorts, Google Ads + Meta Ads + SEO/GEO MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ 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
Official PostHog MCP Server for product analytics, feature flags, experiments, and more.
Turn long videos into viral vertical shorts and publish them to TikTok, Instagram and YouTube.
Google Ads, Meta Ads, Google Analytics (GA4) & Search Console MCP server by Ryze AI
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。
A Model Context Protocol server that lets AI agents (Claude Code, Claude, Cursor, ChatGPT, Grok, Grok Bot, OpenClaw, Hermes, and any other MCP client) schedule, publish, and review Markaestro posts through the public API. Exact connection steps per client are on https://markaestro.com/developers/agents (?client=cursor, chatgpt, grok, grok-bot, openclaw, hermes, or headless opens that tab).
Every key covers either one brand or every brand in its workspace, chosen when the key is created or at the sign-in consent. A single-brand key works on that brand alone. An all-brands key sees every brand: list_products returns them all, and the agent passes productId to create_post, create_posts, list_posts, and create_evergreen_queue, and to the analytics tools to report on one brand instead of the whole workspace.
| Tool | What it does |
|---|---|
list_products | The brands this key can act on (one, or all in the workspace) and their connected channels |
list_destinations | Publishable destinations of the brand (pages, accounts) with ids |
get_brand_profile | A brand's description, voice, and visual identity (read-only) |
list_posts, get_post | Read posts by status, page through with cursor |
create_post | Save a draft, or schedule when scheduledAt is set |
update_post | Edit a draft or scheduled post: caption, media, one channel's settings, or its time |
publish_post | Queue an immediate publish; returns a job run |
mark_post_posted | Record that a person posted a manual-reminder or TikTok-inbox post |
delete_post | Delete a draft, or cancel a post before it reaches any platform; published posts are refused |
bulk_posts | Reschedule or restatus up to 25 posts |
create_posts | Up to 25 posts in one call, per-item results |
upload_media | Upload from a file path, URL, or data URL; returns the asset id |
list_media, get_media | Uploaded assets, processing state, reference counts |
get_analytics | Brand performance over a window: totals, channels, daily series, top posts, heatmap, insights. Covers posts published through Markaestro and posts published directly on the platform |
list_post_analytics | Every post in the window with its latest metrics and source, sortable by views, reach, engagements, or engagement rate |
get_post_analytics_history | The 1h to 90d metric snapshots of one post, with growth between stages |
refresh_analytics | Pull live metrics from the platforms now (a few calls a minute) |
suggest_post_times | The brand's best posting windows, learned from its own history |
get_job_run, list_job_runs | Follow a publish to succeeded or failed |
get_channel_rules | Per-channel media, caption, and delivery-mode rules |
get_tiktok_posting_options | The TikTok creator's live privacy levels and interaction options, needed for a Direct Post |
The Evergreen tools (preview_, create_, get_, list_, update_, activate_, pause_, and resume_evergreen_queue, list_evergreen_runs, get_evergreen_analytics) manage proven recurring content.
Agents manage social media and nothing else: account settings, billing, team, API keys, webhooks, and channel connections are not exposed, and no tool deletes a published post, takes one down from a platform, or archives an Evergreen queue. Those stay with the user in Markaestro. The same rule holds at the REST layer for a key issued through the agent sign-in: it cannot remove a published post, take one down from a platform, or manage webhooks (FORBIDDEN_AGENT_CONNECTION). A key a person mints in Settings keeps the full REST surface its scopes allow.
Also served: the markaestro://channel-rules resource and a schedule_post prompt that walks an agent through a safe scheduling flow.
Posting is draft-first. create_post without scheduledAt never publishes; publish_post is the only tool that publishes now, and its description tells the agent to confirm with the user first.
Hosted (nothing to install, nothing to paste). Markaestro serves the same tools over Streamable HTTP at https://markaestro.com/api/public/v1/mcp. Add it with no credentials and the first tool call opens the browser: sign in, pick the workspace and brand, click Allow. The client receives an API key bound to that brand and refreshes it on its own.
claude mcp add --transport http markaestro https://markaestro.com/api/public/v1/mcp
This is standard OAuth 2.1 (PKCE, dynamic client registration, discovery at /.well-known/oauth-protected-resource and /.well-known/oauth-authorization-server), so claude.ai, Cursor, and other MCP clients connect the same way. Connected agents are listed and revoked in Settings, API.
For headless or CI use, pass a workspace API key as a bearer header instead:
claude mcp add --transport http markaestro https://markaestro.com/api/public/v1/mcp \
--header "Authorization: Bearer mk_live_..."
{
"mcpServers": { "markaestro": { "type": "http", "url": "https://markaestro.com/api/public/v1/mcp", "headers": { "Authorization": "Bearer mk_live_..." } } } }
Send x-markaestro-read-only: 1 as an extra header to get only the reading tools.
Local package. Run the server on your machine over stdio, which also lets upload_media read local files:
products.read, posts.read, posts.write, media.write, and posts.publish if it may publish), and prefer a test key while you evaluate.MARKAESTRO_API_KEY.claude mcp add markaestro -e MARKAESTRO_API_KEY=mk_live_... -- npx -y @markaestro/mcp
{
"mcpServers": { "markaestro": { "command": "npx", "args": ["-y", "@markaestro/mcp"], "env": { "MARKAESTRO_API_KEY": "mk_live_..." } } } }
| Variable | Required | Default |
|---|---|---|
MARKAESTRO_API_KEY | yes | n/a |
MARKAESTRO_BASE_URL | no | https://markaestro.com |
MARKAESTRO_READ_ONLY | no | unset; 1 registers only reading tools |
Idempotency-Key on every mutation, minted once per call, so a retried request replays instead of double-posting.429 and transient 5xx responses using the server's Retry-After.PUT to storage, finalize) and never sends the API key to the storage URL.code, any per-channel issues, and a hint about what to change.The skill and the hosted server ship together as a plugin:
claude plugin marketplace add markaestro/markaestro-agents
claude plugin install markaestro@markaestro
Maintainers: the full release runbook (every surface, the version files, and the exact commands) is docs/operations/mcp-release.md in the Markaestro app repository. Summary:
| Surface | How it ships |
|---|---|
Hosted MCP (/api/public/v1/mcp) | Part of the Next.js app; deploys on push to main like every route |
@markaestro/mcp on npm | cd mcp && npm version && npm publish (public scoped package; prepublishOnly builds). Bump src/version.ts with it |
| Plugin and skill | Mirrored to the public repo markaestro/markaestro-agents with node scripts/sync-agents-repo.mjs , then pushed there; claude plugin marketplace add markaestro/markaestro-agents reads it. The skill alone can be copied to ~/.claude/skills/markaestro |
MCP Registry (com.markaestro/mcp) | After the npm publish of the same version: mcp-publisher login http --domain markaestro.com --private-key then mcp-publisher publish from mcp/. The public key is served at /.well-known/mcp-registry-auth |
Glama (markaestro/markaestro-agents) | Admin, Dockerfile: build step npm install -g @markaestro/mcp@ , CMD markaestro-mcp; Build, then Create Release |
cd mcp
npm install npm run build MARKAESTRO_API_KEY=mk_test_... MARKAESTRO_BASE_URL=http://localhost:3000 npm run smoke # local stdio MARKAESTRO_API_KEY=mk_test_... MARKAESTRO_BASE_URL=http://localhost:3000 npm run smoke -- --remote # hosted endpoint
Unit tests live in src/__tests__ and run with the repository's npm test. The smoke script starts the built server over stdio, lists tools, reads the brand, creates a draft, reads it back, and deletes it. Nothing is published.