AdsAgent 三渠道托管 MCP 的公共 Claude 插件 + 技能包：Meta、Google Ads 和 TikTok。
分发划分（重要）：
分发渠道 | 说明 | 本仓库？ |
Claude 插件（自托管市场） | 技能 + 根 | 是 |
Anthropic Connectors 目录 | 仅托管 MCP 服务器列表 | 否 — 需在 |
官方 GitHub 仓库： github.com/adsagents/adsagent-ai-skills
网站： adsagent.md
官方链接中心： adsagent.md/connect
技能包登录页： adsagent.md/skills
支持： support@adsagent.md
当前合约版本：0.7.64。插件标识符为 adsagent（市场键 adsagent）。
新的 Meta 连接默认为 v2 产品配置文件；所有三个托管端点
协商现代 MCP 2026-07-28 无状态发现，同时保留支持
传统初始化客户端。
版本历史记录在 CHANGELOG.md 中。
本地辅助脚本 scripts/update_reminder.py 比较严格语义版本，并仅在 $XDG_CACHE_HOME/adsagent-ai-skills/update-reminder-v1.json（或 ~/.cache/...）中存储带边界的版本/时间戳状态。缓存失败不会阻塞 MCP 工作。
一个公共 Claude 插件市场包：行为技能加上通过 .mcp.json 提供的托管 MCP URL。
针对 Claude Code、Cursor、Codex 及其他支持 MCP 客户端的行 为指南。
一个可靠性和安全层，告诉代理何时重试、何时等待以及何时停止。
用于 AdsAgent 用户入门和代理行为指引的版本化 GitHub 分发。
针对 AI 代理的数据最小化合约，禁止其将 AdsAgent 扫描为原始数据库。
Related MCP server: synter-mcp-server
不是 Anthropic Connectors 目录 MCP 列表（该列表已在托管服务器上单独注册）。
不是完整的 MCP 工具参考。
不是 SDK。
不是本地传输中继。
不是 AdsAgent 后端路由、模式、数据库表或内部诊断的披露。
对于 Claude Code 插件安装，OAuth MCP 设置来自此仓库的 .mcp.json。
对于不支持插件的客户端，AdsAgent 仪表盘安装提示仍为
手动后备方案：
AdsAgent dashboard -> Settings -> MCP Access -> Copy install prompt仅当您未安装 Claude 插件包时，才使用该复制的提示。 此仓库在 MCP 连接建立后教授代理行为。
技能 | 目的 |
| 将 AdsAgent 请求路由到设置、可靠性、洞察或复制工作流。 |
| 通过 AdsAgent 仪表盘安装提示进行连接，并验证 Meta、Google Ads 或 TikTok 的就绪状态。 |
| 检查并安全配置通知渠道和 Meta Ads Webhooks。 |
| 遵循重试、回退、会话刷新和并发限制。 |
| 设计、创建、验证、更新、暂停和删除代理拥有的计划任务，避免将提醒与执行证明混淆。 |
| 在不过载服务器的情况下询问性能和 MMP 问题。 |
| 在确认和操作员审核安全的前提下复制或比较 Meta 广告。 |
| 通过 Google Ads MCP 询问 Google Ads 客户、MCC、搜索、PMax 和性能问题。 |
| 读取 TikTok 性能并安全准备原生创意、广告组和广告组附加工作流。 |
代理客户端加载每个技能描述以进行发现，但应仅加载
所选 SKILL.md 的主体。每个入口点均有意保持小巧，并链接
到本地参考文件，这些文件仅在所选工作流需要
这些细节时才读取。
docs/ 下的文件是面向人类的产品和操作员文档。
它们不是自动代理上下文，也不属于技能参考
遍历。代理行为合约位于 skills/ 下，通过所选的 SKILL.md 访问。
使用 AdsAgent 的代理应默认以 Markdown 格式回答：
## Answer
One-sentence answer.
## Scope
- Date:
- Entity:
- Grouping:
- Attribution / channel:
## Results
| Metric | Value |
| --- | ---: |
## Notes
- Data freshness:
- Limits or missing fields:
- Next safe action:不要将 JSON、CSV、隐藏诊断、原始行或每个返回字段倾倒到聊天中。将响应清理为面向操作员的表格和简短要点。如果需要法证级别的原始检查，请创建操作员交接，而不是让原始行成为代理的回答。
此仓库有意记录结果和代理行为，而非完整的内部接口。代理应：
在连接后阅读实时 AdsAgent MCP 指南。
通过经过身份验证的 MCP 会话使用可用工具。
避免猜测隐藏的有效负载字段。
避免探测被拒绝的请求。
在操作员审核响应时停止，并要求 AdsAgent 操作员检查内部诊断。
在发出请求之前使用最小的安全数据计划。
优先使用分组摘要和清理后的细分，而非原始行。
外部代理合约是：提出明确问题、遵守限制、在写入前确认、使用仪表盘提供的入门指南。
此仓库仅包含客户端可读的行为包。AdsAgent 服务器源代码、凭证、模式、路由逻辑和操作诊断信息不在此处分发。
该包是专有的，所有权利归 adsagents LLC 所有。公共 GitHub 托管允许用户查看和 Fork 此仓库（依据 GitHub 服务条款），但 Fork 或本地副本不授予任何额外的知识产权许可，除非 LICENSE.md 中规定的有限 Anthropic Claude 插件目录镜像权。未授予任何其他权限以重新分发、镜像、出售、再许可、发布修改版本、创建衍生作品、从此包训练竞争产品或将 Fork 表示为官方版本。请参阅 LICENSE.md 和 NOTICE.md。
Use AdsAgent to list my connected Meta products, Google Ads customers, or TikTok advertisers, then ask which scope's today data I want to inspect.For Google Ads, inspect agent_method_profile, pick an enabled non-manager customer, and use one cached insights_query_consistent request when the profile is advertised.For TikTok, inspect agent_method_profile and use one insights_query_consistent scopes request when advertised; otherwise use the native batch overview fallback.Prepare a copy of this winning Meta ad into the target account, but ask me for confirmation before creating anything.Group these distinct Meta Ads by language into the requested Campaign and AdSet layout. Prepare one grouped_plan, show every settings_source_ad_id and geography override, and wait for my approval before confirming once.更多示例见 docs/examples.md。
运行本地发布合约和测试：
python scripts/validate_tri_channel_pack.py
python -m pytest -q发布验证针对 contracts/manifests/ 中三个已提交的快照进行失败关闭。每个快照从已提交的服务工件逐字节复制，并锁定到其渠道、源修订版、公共工件路径、元数据和 SHA-256，记录在 contracts/manifests/provenance.json 中。CI 不发起实时网络请求。
python scripts/validate_public_tool_manifests.py操作员可以在服务清单更改后确定性地更新所有三个快照。该命令拒绝未提交、脏的、缺失的或合约不兼容的源，并且从不从网络获取：
python scripts/sync_public_tool_manifests.py \
--source meta=/path/to/meta-tools.json \
--source google=/path/to/google-tools.json \
--source tiktok=/path/to/tiktok-tools.json所有三个源都是强制性的。缺失引用的工具、未经证明的必需能力或门控、过时的来源摘要或缺失的渠道，都会导致发布验证失败。--allow-missing 仅用于明确的本地诊断，不在发布 CI 中使用。
此仓库作为 adsagent Claude 插件（技能 + .mcp.json MCP URL）发布。
GitHub 仓库名称保持为 adsagent-ai-skills。
claude plugin marketplace add adsagents/adsagent-ai-skills
claude plugin install adsagent@adsagent更新现有用户范围的安装：
claude plugin update --scope user adsagent@adsagent如果 claude plugin list 显示重复的本地和用户安装，请保留用户范围：
claude plugin uninstall --scope local adsagent@adsagent安装或更新后启动一个新的 Claude Code 会话。
{
"extraKnownMarketplaces": {
"adsagent": {
"source": {
"source": "github",
"repo": "adsagents/adsagent-ai-skills"
}
}
},
"enabledPlugins": ["adsagent@adsagent"]
}安装后，对 /mcp 中显示的每个 MCP 服务器（Meta、Google、TikTok）进行身份验证。
不要将 headers.Authorization 添加到 .mcp.json 中；OAuth 必须保持为认证路径。
旧版安装使用了 adsagent-ai-skills@adsagent-ai-skills 或
adsagent-meta-ai-skills@adsagent-meta-ai-skills。市场声明重命名
为 adsagent@adsagent。迁移后，删除旧版重复项：
claude plugin uninstall --scope user adsagent-ai-skills@adsagent-ai-skills
claude plugin uninstall --scope user adsagent-meta-ai-skills@adsagent-meta-ai-skillscodex plugin marketplace add adsagents/adsagent-ai-skills
codex plugin add adsagent@adsagent刷新：
codex plugin marketplace upgrade adsagent安装或升级后启动一个新的 Codex 会话。
skills/ 中的技能使用标准的 Agent Skills 布局
（skills/<name>/SKILL.md 带 YAML 前言）。仅使用技能
（不带插件 MCP 包）的客户端可以手动克隆：
git clone https://github.com/adsagents/adsagent-ai-skills.git ~/.codex/skills/adsagent-ai-skills这些客户端仍需要单独的 MCP 连接（仪表盘安装提示或 Connectors 目录）。插件路径是一步式技能 + MCP 包。
然后，仅当您需要为非插件客户端进行仪表盘 OAuth/令牌设置时，才打开 AdsAgent：
Settings -> MCP Access -> Copy install prompt将复制的提示粘贴到新聊天中，当不使用插件包时。 该提示提供托管的 HTTP MCP URL，用于：
Meta default: https://adsagent.md/mcp/v2
Meta legacy fallback: https://adsagent.md/mcp
Google Ads: https://google.adsagent.md/mcp
TikTok: https://tiktok.adsagent.md/mcp仅限托管 HTTP MCP。
对于新的 Meta 连接，使用 https://adsagent.md/mcp/v2；/mcp 是旧版回退。
不要在本地运行 AdsAgent MCP 代码。
除非 AdsAgent 仪表盘明确说明，否则不要使用本地中继。
在客户端支持的情况下缓存连接设置。
保持每个令牌的 MCP 并发性有界。
遵守 Retry-After。
从 HTTP 头部、顶层 data 或 JSON-RPC error.data 中解析 Retry-After。
尊重 mcp_concurrency_limited，并添加等待和抖动。
尊重 mcp_fanout_detected，切换为使用平台批量概览工具，而不是重试被阻止的单范围请求。
当 agent_method_profile.profile_id=adsagent_agent_methods_v1 且其一致性读取存在于客户端本地目录中时，对三个平台使用一个 insights_query_consistent 请求，包含 scope 或有序的 scopes。
如果没有该配置文件，或者其广告的一致性读取仅在客户端本地目录中缺失，则使用配置文件的指定原生回退或文档化的服务端工具：Meta/TikTok 使用 insights_query_batch_overview，Google 使用 google_ads_insights_overview_batch。不要因本地选择器缺失而报告服务端注册失败。
首先查询聚合数据，切勿从共享工具名称推断跨平台能力对等性。
从响应中报告服务端计算的总数；不要对当前可见的行进行求和。
仅当 meta.complete=true 时信任总数；缺失的范围是未知的，绝不视为零。
轮询队列任务直到 terminal=true，并返回工件链接，而不是原始 CSV。
当服务端通告直接任务引用时，直接使用 tasks_get_status(task_ref=...) 轮询队列工作。
QuickCreate 确认令牌为一次性使用，15 分钟后过期。检查 expires_at；在 confirm_token_invalid 后，重新准备，显示新的摘要，并获取明确的新批准。
使用 tasks_get_status(task_ref=..., response_mode=compact) 轮询 Meta 创建任务。在 no_create_permission 时，引导用户到 /dashboard/assets/fb-users；切勿更改客户权限或自动重试失败的创建操作。
在常规用户对话中避免原始行读取。
数字使用 Markdown 表格。
在广告创建或修改前进行确认。
对于多个不同的源广告，使用 grouped_plan；切勿通过客户端的一系列复制变异来模拟它。
在操作员审查错误时停止。
当错误包含 support_ref 时，保留并原样显示以供支持。这不是授权；切勿发明、修改、枚举或将其替换为令牌、请求体或日志。
官方网站：https://adsagent.md
保留所有权利。参见 LICENSE.md。
Return AdsAgent hosted HTTP MCP URLs from this repo's mcp.json.
Use this when a client needs the real Meta, Google Ads, or TikTok ads MCP endpoints. Those services require AdsAgent OAuth on the hosted URLs.
This docs server does not implement ads tools, does not accept tokens, and does not proxy those endpoints. Copy the https URLs into an MCP client and authenticate against AdsAgent hosted services.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the source (mcp.json), the OAuth requirement for hosted URLs, and the server's limitations (no implementation, no token acceptance, no proxying). This sets accurate expectations for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, with the primary action front-loaded in the first sentence. Each sentence contributes either usage guidance or critical limitations with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema and no annotations, the description is complete: it explains what is returned, when to use it, and what it does not do. An agent can safely and correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema already makes this clear with 100% coverage. The description adds no parameter details, which is fine; a baseline of 4 is appropriate for a no-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Return AdsAgent hosted HTTP MCP URLs from this repo's mcp.json.' This clearly states what the tool does and distinguishes it from sibling tools that operate on skills and readmes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'Use this when a client needs the real Meta, Google Ads, or TikTok ads MCP endpoints,' and then clarifies what the docs server does not do (implement ads tools, accept tokens, proxy endpoints). This provides both a when-to-use and a when-not context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return this skill-pack VERSION and a README.md identity excerpt.
Use this to confirm pack version and the public 'what this is / is not' wording, including that a Glama or Docker image of this repo is not the hosted AdsAgent ads backend.
The excerpt stops before the per-skill table. It does not include secrets.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It usefully states what is returned (VERSION and README identity excerpt), what is excluded (per-skill table, secrets), and the identity nuance about the repo not being the hosted AdsAgent ads backend. It does not describe output format or error conditions, but for a zero-parameter read tool the disclosed boundaries are strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: the main action is stated in the first sentence, usage guidance follows, and boundary conditions are summarized in two short sentences. Every sentence earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema and no annotations, the description fully covers what the agent needs: what the tool returns, its intended use, and its explicit exclusions. The nuance about the Glama/Docker image not being the hosted AdsAgent backend also prevents a plausible misunderstanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, so parameter explanation is unnecessary. The description instead focuses on the meaningful output semantics, which is the right trade-off for an argument-less tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb and resource: 'Return this skill-pack VERSION and a README.md identity excerpt.' This clearly distinguishes the tool from siblings like get_skill, get_hosted_mcp_urls, and list_skills by describing a unique output. The additional clarification about 'what this is / is not' wording further pins down its exact purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this to confirm pack version and the public wording,' giving a clear and direct usage context. It does not, however, name alternative sibling tools or state when not to use them, so it falls short of full exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return one skill's SKILL.md and optional named reference files.
Use this after list_skills when you need the full public instructions for a single skill. Pass references only for Markdown files that live in that skill folder (progressive-disclosure contracts).
Rejects unknown skill ids and any path that leaves the skill directory. This is documentation retrieval, not a live ads API.
| Name | Required | Description | Default |
|---|---|---|---|
| skill_id | Yes | Skill folder name under skills/, for example meta-insights or adsagent-router. | |
| references | No | Optional skill-local .md filenames to include with SKILL.md, such as query-contract.md. Paths must stay inside that skill folder. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses validation behavior ('Rejects unknown skill ids and any path that leaves the skill directory'), the read-only nature ('documentation retrieval, not a live ads API'), and the progressive-disclosure contract for references. It doesn't cover errors for nonexistent reference files, auth, or rate limits, but for a simple retrieval tool these are not critical omissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with zero filler. The core purpose is front-loaded in the first sentence, usage guidance follows in the second, and the final sentence provides validation and identity context. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read-only tool with no output schema and no annotations, the description covers the key context: what is returned, when to use it, the progressive-disclosure reference convention, and validation rules. It does not specify the exact response structure or behavior when an in-folder reference file is missing, but the tool is simple enough that the description is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already thoroughly documents both skill_id and references, including examples and path constraints. The description reinforces these semantics with 'progressive-disclosure contracts' and the rejection of path escape, but it does not add substantial new parameter-level meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific action and resource: 'Return one skill's SKILL.md and optional named reference files.' It is clearly distinguished from list_skills (which lists skills) by saying to use it after list_skills for the full public instructions of a single skill, and from the live ads API identity statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this after list_skills when you need the full public instructions for a single skill,' giving a clear when. It also instructs when to pass references (only for Markdown files in that skill folder) and that invalid ids/paths are rejected. However, it does not explicitly compare to the sibling tools get_pack_readme or get_hosted_mcp_urls, so it falls short of a full when-not/alternatives roadmap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List public AdsAgent skills shipped in this repository.
Use this first when you need a catalog of documentation skills (router, setup, reliability, notifications, scheduled tasks, Meta, Google Ads, TikTok) before opening a specific SKILL.md.
Returns each skill id, YAML frontmatter description, and first Markdown heading. This tool only reads local files under skills/. It does not connect to Meta, Google Ads, or TikTok and does not run campaigns.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does so well. It discloses that the tool 'only reads local files under skills/, does not connect to Meta, Google Ads, or TikTok and does not run campaigns,' which prevents the agent from expecting external side effects. It also describes the return contents, giving useful behavioral expectations beyond a simple 'list' label.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, front-loading the main action and resource. Each sentence earns its place: what it returns, when to use it, and what it does not do. No redundant or vague language.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read-only listing tool with no output schema, the description is complete. It names the domain of skills, gives the intended first-use pattern, describes return fields, and explicitly scopes its behavior. An agent has everything needed to invoke it and interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there are no parameter semantics to document. The description still usefully explains the output shape, which is more relevant for this tool. A baseline of 4 is appropriate since parameter documentation is not needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'List public AdsAgent skills shipped in this repository.' It clearly distinguishes this catalog-listing tool from siblings like get_skill, which opens a specific SKILL.md, and from get_hosted_mcp_urls/get_pack_readme. The scope is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this first when you need a catalog of documentation skills... before opening a specific SKILL.md,' providing a clear when-to-use directive. It does not spell out when-not-to-use or name alternatives, but the context is strong enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.7.67get_hosted_mcp_urlsget_pack_readmeget_skilllist_skillsScored across 4 tools
Each tool has a clear, distinct responsibility: list_skills catalogs available skills, get_skill retrieves a specific skill's documentation, get_pack_readme returns pack identity/version, and get_hosted_mcp_urls exposes hosted endpoint URLs. There is no meaningful overlap or ambiguity between them.
Tool names follow a predictable verb_noun pattern: get_* for single-item retrieval and list_skills for collection retrieval. The naming is consistent, descriptive, and easy to infer.
Four tools is well-scoped for a documentation/skill-pack server. Each tool earns its place and covers a necessary retrieval function without unnecessary bloat.
The tool surface covers the full documentation workflow: discover available skills, fetch individual skill details, confirm pack identity/version, and retrieve hosted MCP URLs. There are no obvious dead ends for the stated documentation-only purpose.
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