AEP MCP Server
AEP MCP 服务器
两个 MCP 服务器,让 Claude(以及任何兼容 MCP 的客户端)能够以自然语言访问 Adobe Experience Platform、Adobe Journey Optimizer 和 Real-Time CDP。
服务器 | 文件 | 工具数量 | 描述 |
AEP(自定义构建) |
| 137+ | 基于 FastMCP 构建的完整 AEP/AJO API 覆盖 |
RT-CDP(Adobe 官方代理) |
| 18 | 代理 Adobe 官方 |
快速开始
1. 运行设置脚本
./setup.sh这将创建一个 .venv,安装所有依赖项,安装 pre-commit 钩子,并打印出要粘贴的确切 MCP 配置 JSON——包括您机器上正确的绝对 venv Python 路径。
Windows: 手动运行这些步骤——
python3 -m venv .venv,.venv\Scripts\activate,pip install -r requirements.txt。
2. 配置凭据
从 Adobe Developer Console → 项目 → OAuth 服务器到服务器 填写您的凭据:
# orgs.json was created by setup.sh — edit it now或者使用环境变量(单组织回退):
cp .env.example .env
# edit .env3. 注册到 Claude Code
将 setup.sh 打印的 JSON 粘贴到 .claude/mcp_servers.json 中,例如:
{
"aep": {
"command": "/path/to/aep-mcp-server/.venv/bin/python",
"args": ["/path/to/aep-mcp-server/server.py"]
}
}始终使用 venv Python 路径——MCP 客户端在任何活动 shell 之外启动服务器,因此裸的
python3将找不到已安装的包。
4. 运行
python3 server.py # AEP server, default org profile
AEP_PROFILE=MyClient python3 server.py # start with a specific profileRelated MCP server: Fourth Brain Demo
多组织配置
orgs.json 支持多个命名配置文件——在跨不同 Adobe 组织或沙盒工作时非常有用:
{
"default": "ClientA",
"profiles": {
"ClientA": {
"client_id": "...",
"client_secret": "...",
"api_key": "...",
"org_id": "XXXX@AdobeOrg",
"sandbox": "prod",
"sandboxes": {
"dev": "my-sandbox-dev",
"prod": "my-sandbox-prod"
}
},
"ClientB": {
"client_id": "...",
"client_secret": "...",
"api_key": "...",
"org_id": "YYYY@AdobeOrg",
"sandbox": "prod"
}
}
}在运行时使用 switch_org_profile 工具切换组织,或通过设置 AEP_PROFILE 在启动时切换。令牌缓存按配置文件维护。
服务器 1 — AEP MCP (server.py)
基于 FastMCP 构建。所有工具都接受可选的 sandbox 参数;如果省略,则使用活动配置文件的默认沙盒。
数据集与批次
list_datasets · get_dataset · create_dataset · get_batch · list_batches · get_sandbox · list_sandboxes · reset_sandbox
XDM 模式注册表
list_schemas · get_schema · create_schema · enable_schema_for_profile · list_field_groups · get_field_group · create_field_group · list_classes · list_data_types · list_descriptors · create_descriptor
实时客户资料与身份
get_profile_by_identity · get_identity_cluster · list_identity_namespaces · get_identity_namespace · list_merge_policies · list_profile_export_jobs · get_profile_export_job
细分/受众
list_segments · get_segment · create_segment · delete_segment · list_segment_jobs · get_segment_job · create_segment_job · list_streaming_jobs
查询服务
list_queries · get_query · run_query · cancel_query · list_query_runs · list_query_templates · get_query_template · create_query_template · list_scheduled_queries
AJO — 历程与营销活动
list_journeys · get_journey · list_journey_versions · list_campaigns · get_campaign
AJO — 优惠决策
list_offers · get_offer · list_placements · list_collections · list_offer_activities · get_offer_activity · list_ranking_formulas · create_eligibility_rule
流程服务(源与目标)
list_connections · get_connection · list_connection_specs · get_connection_spec · list_dataflows · get_dataflow · list_flow_runs · get_flow_run · list_source_connections · get_source_connection · list_target_connections · get_target_connection
可观测性洞察与警报
get_metrics · list_alert_subscriptions · get_alert_subscription · get_alerts_by_feature · list_alert_notifications · subscribe_alert
数据卫生
list_dataset_expirations · get_dataset_expiration · create_dataset_expiration · cancel_dataset_expiration · list_record_delete_orders · get_record_delete_order · create_record_delete_order · get_hygiene_quota
数据准备(映射)
list_mapping_sets · get_mapping_set · create_mapping_set · preview_mapping_set · list_mappings · get_mapping · validate_mapping_expression · list_data_prep_functions
计算属性
list_computed_attributes · get_computed_attribute · create_computed_attribute · update_computed_attribute
访问控制(ABAC)
list_roles · get_role · list_role_subjects · list_role_policies · list_policies · get_policy · get_effective_policies · list_available_permissions · list_users · get_user_roles
客户历程分析(CJA)
CJA 工具使用数据视图 ID 而不是沙盒。
cja_list_connections · cja_get_connection · cja_list_data_views · cja_get_data_view · cja_list_dimensions · cja_list_metrics · cja_list_projects · cja_get_project · cja_create_project · cja_update_project · cja_delete_project · cja_list_filters · cja_get_filter · cja_create_filter · cja_update_filter · cja_delete_filter · cja_list_calculated_metrics · cja_get_calculated_metric · cja_create_calculated_metric · cja_update_calculated_metric · cja_delete_calculated_metric · cja_list_annotations · cja_create_annotation · cja_delete_annotation · cja_run_report
组织与多组织管理
list_org_profiles · get_current_org · switch_org_profile · switch_sandbox
服务器 2 — RT-CDP 代理 (rtcdp_proxy.py)
一个轻量级的 stdio→HTTPS 代理,将工具调用转发到 Adobe 官方的 Real-Time CDP MCP 服务器,地址为 rtcdp-mcp.adobe.io。认证头来自活动的 orgs.json 配置文件,因此 switch_org_profile 可跨两个服务器工作。
通过 .env 配置上游 URL(可选——默认为 Adobe 的端点):
RTCDP_MCP_URL=https://rtcdp-mcp.adobe.io/mcp注意: Adobe 的 RT-CDP MCP 服务器是一个受限功能。请联系您的 Adobe 代表以获取访问权限。
工具(从 Adobe 代理)
search_audiences · preview_audience_membership · inspect_audience_evaluation_jobs · inspect_audience_export_jobs · search_destination_connectors · search_destination_accounts · search_destination_flows · search_destination_input_connections · search_destination_output_connections · search_source_connectors · search_source_accounts · search_source_flows · search_source_input_connections · search_source_output_connections · search_identity_namespaces · search_merge_policies · search_organizations · inspect_flow_runs
项目结构
server.py # AEP FastMCP entrypoint
rtcdp_proxy.py # RT-CDP stdio→HTTPS proxy
auth.py # Auth + HTTP helpers; multi-org profile state
orgs.json # Your credentials — GITIGNORED, never commit
orgs.example.json # Template for orgs.json
.env / .env.example # Fallback single-org config
requirements.txt
hooks/pre-commit # Blocks credential commits
scripts/install_hooks.py # Installs the pre-commit hook
tools/
datasets.py # Catalog Service: datasets, batches, sandboxes
schemas.py # Schema Registry: XDM schemas, classes, field groups
profiles.py # Real-Time Customer Profile, identity, merge policies
segments.py # Segmentation: definitions, jobs, streaming
query.py # Query Service: ad-hoc SQL, templates, scheduled
ajo.py # AJO: journeys, campaigns, offers, eligibility rules
cja.py # Customer Journey Analytics
flows.py # Flow Service: connections, dataflows, flow runs
observability.py # Observability Insights: metrics, alerts
data_hygiene.py # Data Hygiene: dataset TTL, record deletes
data_prep.py # Data Prep: mapping sets, expression validation
computed_attributes.py # Computed Attributes
access_control.py # ABAC: roles, permissions, effective policies
orgs.py # Multi-org: list/switch profiles and sandboxes
usage_logger.py # @track decorator — logs tool calls to CSV添加新工具模块
创建
tools/new_domain.py,包含一个register(mcp)函数添加到
server.py:导入它并调用new_domain.register(mcp)遵循
CLAUDE.md中的工具模式
认证流程
auth.py 首先检查 orgs.json 配置文件,然后回退到 .env 环境变量。
OAuth S2S(推荐):设置
client_id+client_secret——令牌在过期前自动刷新静态令牌(开发/测试):设置
access_token——无自动刷新
要求
mcp[cli]>=1.3.0
httpx>=0.27.0
python-dotenv>=1.0.0This server cannot be installed
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