Quick Space Migrator
MCP server that migrates Amazon Quick Suite resources (Spaces, Chat Agents, Action Connectors, and S3 Knowledge Bases) between AWS accounts, preserving permissions and linkages, with idempotency and preview dry-run support.
README
Quick Space Migrator — Amazon Bedrock AgentCore MCP Server
Migrate Amazon Quick Suite resources — Spaces, Chat Agents, Action Connectors, and S3 Knowledge Bases — between AWS accounts through a Model Context Protocol (MCP) server hosted on Amazon Bedrock AgentCore Runtime. The server can be driven directly from Amazon Quick (as an action connector) or from any MCP-compatible client.
The migrator recreates every link exactly as it exists in the source — agents are created with their Spaces and Action Connectors attached, and knowledge bases are wired back to their spaces. There is no manual re-linking step. Permissions are not hard-coded: the server describes each source resource's permissions and replays the identical actions in the target, remapping principals to a real registered user in the target account.
Problem statement
Promoting a Quick Space from one account to another (for example, dev → prod)
by hand is slow and error-prone:
- Each Space, Agent, Connector, and Knowledge Base must be recreated individually with the correct configuration.
- Resource permissions must be re-granted, with principals remapped to the target account's registered users.
- Every link (agent ↔ space, connector ↔ space, KB ↔ space) has to be rebuilt so the migrated app behaves like the original.
- S3-backed knowledge bases need their bucket, bucket policy, and data source provisioned before the KB can be attached.
Doing this repeatedly across environments is exactly the kind of deterministic, idempotent work that should be automated.
What this solution provides
- A single
migrate_spacesMCP tool that performs the full cross-account migration in one call, and a read-onlypreview_migrationtool for a dry run. - Idempotency — every resource is created-or-updated, so re-running a migration converges instead of producing duplicates.
- Faithful linkage — agents, connectors, and knowledge bases are linked to their spaces exactly as in the source.
- Permission fidelity — permissions are copied by describing the source and replicating the exact actions, with principals resolved to a real user in the target account.
- Infrastructure as code — CloudFormation templates for the IAM roles, VPC network, and the AgentCore runtime (Cognito JWT auth + VPC network mode).
Architecture

| Component | Account | Responsibility |
|---|---|---|
| AgentCore Runtime (MCP server) | Central (Runner) | Hosts server.py; assumes into source & target; orchestrates the migration. Runs in VPC network mode with a Cognito JWT authorizer. |
| Amazon Cognito | Central (Runner) | User pool + resource server + machine-to-machine app client. Issues the JWT (client-credentials grant, scope invoke) that callers present to AgentCore. |
| Runner execution role | Central (Runner) | AgentCore's execution role: Bedrock InvokeModel, CloudWatch Logs, X-Ray, and sts:AssumeRole into the source & target roles. |
quick-space-migrator-role |
Source | Read-only QuickSight describe/list permissions + KB read. |
quick-space-migrator-role |
Target | Read-write QuickSight create/update permissions + KB and S3 write + ListUsers for principal resolution. |
Migration flow (migrate_spaces)
- Resolve spaces — expand
"all"or the comma-separated space IDs. - Read source spaces — describe each space and its resources.
- Discover agents — find agents linked to those spaces.
- Create spaces in the target (update-on-exists).
- Create connectors — authentication config is sanitized to the create (write) model with placeholder secrets; connectors are re-authenticated in the target UI.
- Migrate S3 knowledge bases — create the target bucket
(
knowledge-base-<env>-<account>) + bucket policy + data source + KB, then copy KB permissions and attach to the target space. - Create agents linked to their spaces and connectors — exactly as in the source.
Data note: the migrator provisions the target KB bucket and registers the knowledge base, but does not copy the S3 objects themselves. Sync the documents (e.g.
aws s3 sync) and trigger a KB ingestion separately. See docs/knowledge-base-iam-setup.md.
Repository layout
quick-space-migrator-mcp/
├── src/
│ └── server.py # The MCP server (the only first-party runtime file)
├── infrastructure/ # CloudFormation templates (deploy in this order)
│ ├── runner-role.yaml # 1. Central account: AgentCore execution role
│ ├── quick-migrator-role.yaml # 2. Source & target account cross-account role
│ ├── network.yaml # 3. VPC, subnets, NAT, endpoints, security groups
│ └── agentcore-runtime.yaml # 4. Cognito + AgentCore runtime
├── scripts/ # Deployment automation (wrappers over the templates)
│ ├── build.sh # Package server.py + deps → build/deployment.zip (ARM64)
│ ├── deploy-roles.sh # Deploy runner → source → target roles (ordered)
│ ├── deploy-network.sh # Deploy the VPC network stack
│ └── deploy.sh # Build, upload artifact, deploy the runtime
├── examples/ # Optional helper scripts for testing
│ ├── setup_source.py # Seed a source account with sample spaces/agents/KB
│ └── manage_agent_space.py # Attach/detach a space from an agent
├── docs/
│ ├── knowledge-base-iam-setup.md # KB IAM policy + S3 bucket naming convention
│ └── quick-app-integration.md # Build a Quick App on top of the MCP connector
├── images/
│ └── architecture.svg
├── requirements.txt # Runtime dependencies (resolved at build time)
├── README.md
├── CONTRIBUTING.md
├── CODE_OF_CONDUCT.md
├── THIRD_PARTY_LICENSES
└── LICENSE
No dependencies are vendored into the repository — scripts/build.sh resolves
them from PyPI at package time into a git-ignored build/ directory.
Prerequisites
Install the following locally:
- AWS CLI v2 — configured with credentials/profiles for each account
- Python 3.14 — the AgentCore runtime targets Python 3.14 on Linux ARM64
- Bash and zip
- Three AWS accounts (or three roles): central/runner, source, target (source and target may be the same account for a smoke test)
ARM64 note: AgentCore Runtime runs on AWS Graviton (Linux
aarch64).scripts/build.shusespip --platform manylinux2014_aarch64 --only-binary=:all:so it produces a correct bundle even when run from an Intel or Apple-Silicon Mac.
Deployment
Deploy the stacks in the order below. All commands assume you are in the repository root.
1. IAM roles (runner → source → target)
The runner execution role is created first so the source/target trust policies can reference its ARN directly (no chicken-and-egg). Account IDs are derived automatically from each CLI profile.
./scripts/deploy-roles.sh \
--runner-profile central \
--source-profile source-acct \
--target-profile target-acct \
--artifact-bucket my-agentcore-artifacts
2. VPC network
AgentCore only supports specific Availability Zone IDs (in us-east-1:
use1-az1, use1-az2, use1-az4). The script prints the AZ name→ID mapping so
you can confirm before deploying.
./scripts/deploy-network.sh --az1 us-east-1a --az2 us-east-1b
3. Build + deploy the AgentCore runtime
deploy.sh runs build.sh, uploads the artifact to S3, deploys the Cognito +
runtime stack, and prints the token endpoint and client credentials.
./scripts/deploy.sh \
--artifact-bucket my-agentcore-artifacts \
--source-role-arn arn:aws:iam::<SOURCE_ACCOUNT_ID>:role/quick-space-migrator-role \
--target-role-arn arn:aws:iam::<TARGET_ACCOUNT_ID>:role/quick-space-migrator-role \
--cognito-domain-prefix quick-migrator-<CENTRAL_ACCOUNT_ID> \
--runner-role-stack quick-space-migrator-runner-role \
--network-stack quick-migrator-network
On success the script prints the Runtime ARN, token endpoint, app
client ID/secret, and a ready-to-run curl snippet for obtaining a JWT.
Runtime configuration
The runtime needs only two environment variables (plain-string role ARNs, not secrets):
| Variable | Description |
|---|---|
SOURCE_ROLE_ARN |
quick-space-migrator-role ARN in the source account |
TARGET_ROLE_ARN |
quick-space-migrator-role ARN in the target account |
Everything else (accounts, spaces, envs, QuickSight service role) is passed as a tool input at invocation time.
MCP tools
| Tool | Type | Description |
|---|---|---|
preview_migration |
read-only | Dry run: inventory the spaces, agents, connectors, and knowledge bases that would be migrated. |
migrate_spaces |
read-write | Full migration: create spaces, connectors, knowledge bases, and agents in the target, copy permissions, and recreate every link exactly as in the source. |
migrate_spaces inputs
| Input | Default | Description |
|---|---|---|
source_account_id |
— | 12-digit source AWS account ID |
target_account_id |
— | 12-digit target AWS account ID |
spaces |
"all" |
"all" or comma-separated space IDs |
region |
"us-east-1" |
AWS region |
source_env |
"dev" |
Env segment of the source KB bucket name |
target_env |
"prod" |
Env segment of the target KB bucket name |
qs_service_role |
aws-quicksight-service-role-v0 |
QuickSight service role for the KB bucket policy (no API exists to look this up) |
The tool returns a JSON report with the created spaces, agents, connectors,
knowledge bases, and buckets (each with linked_to_spaces), plus a
skipped_permissions block for any principals that could not be resolved in the
target account.
Integrating with Amazon Quick
Once the runtime is healthy, register it in Amazon Quick as an MCP action connector, then let Quick build an app on top of it. You only need to create two connectors — the migrator MCP connector and (optionally) a Slack connector for notifications; Quick generates the app UI for you from the instructions in docs/quick-app-integration.md.
1. Register the migrator MCP connector
- Type: Action (MCP)
- Endpoint: the AgentCore MCP invocations URL from
deploy.sh:https://bedrock-agentcore.<region>.amazonaws.com/runtimes/<url-encoded-runtime-ARN>/invocations?qualifier=DEFAULT - Network: Public — the AgentCore endpoint is public even in VPC network mode (VPC mode only affects the runtime's outbound traffic).
- Authentication: Service authentication (2LO) with the Cognito client
ID, client secret, token endpoint, and scope printed by
deploy.sh. (Cognito does not support Dynamic Client Registration, so choose service auth rather than the discovery/DCR flow.) - Exposes two actions:
preview_migrationandmigrate_spaces.
2. (Optional) Register a Slack connector
- Type: Action
- Action:
ChatPostMessage— used to post a summary to a channel after a migration completes.
3. Let Quick build the app
Open Amazon Quick, point it at the two connectors, and provide the build specification in docs/quick-app-integration.md. Quick generates the full web app (migration form, preview, confirmation, results with resource-linkage view, Slack notification, and history) — no front-end code to write by hand.
MCP connector tips
- Tool
inputSchemamust be JSON Schema Draft 7 (requiredas an array).- MCP operations have a 60-second timeout — keep individual calls fast.
- Connectors migrated by this tool carry placeholder secrets and must be re-authenticated in the target account's UI.
Testing with the example scripts
Seed a source account with two spaces (one with a Slack connector, one with an S3 knowledge base) and their agents:
python3 examples/setup_source.py \
--account-id <SOURCE_ACCOUNT_ID> \
--region us-east-1 --env dev \
--qs-service-role aws-quicksight-service-role-v0
Inspect or adjust an agent's space links:
python3 examples/manage_agent_space.py show \
--account-id <ACCOUNT_ID> --agent-id analytics-agent
Limitations
- S3 objects are not copied. The migrator provisions the target KB bucket and registers the knowledge base, but you must sync the documents and trigger ingestion yourself.
- Connectors require re-authentication. Secrets are never read from the source; migrated connectors carry placeholders and must be re-authorized in the target UI.
- Principal resolution depends on target registration. Permissions are
granted to a target user only if that identity has been registered in the
target account (i.e. has signed into QuickSight there at least once).
Unresolved principals are reported under
skipped_permissions. - 60-second MCP timeout. Very large migrations (many KBs/agents that sit in a transient state) may approach the MCP socket timeout; the server-side operation still completes.
Security
- No credentials or secrets are stored in this repository. The runtime uses only
two plain-string role ARNs; the Cognito client secret is fetched from the
Cognito API by
deploy.shand never committed. - Cross-account access is least-privilege: the source role is read-only and the target role is scoped to the QuickSight/KB/S3 actions required.
- See CONTRIBUTING.md for how to report a security issue.
Contributing
See CONTRIBUTING.md.
License
This library is licensed under the MIT-0 License. See the LICENSE file. Third-party dependency licenses are listed in THIRD_PARTY_LICENSES.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。