Amazon

AWS

SageMaker Feature Store Runtime MCP server
SageMaker Feature Store Runtime MCP server
SageMaker Feature Store Runtime MCP server
for Claude, ChatGPT, Cursor and your own agents
for Claude, ChatGPT, Cursor and your own agents
for Claude, ChatGPT, Cursor and your own agents

Q: What is the SageMaker Feature Store Runtime MCP server?

It’s a Model Context Protocol server that exposes the SageMaker Feature Store Runtime API operations as tools. Claude, ChatGPT, Cursor or your own agents call them through the Mindflow MCP Gateway.

Q: Do I need an official MCP server from the vendor?

No. Mindflow exposes SageMaker Feature Store Runtime as an MCP server through its native connector, which covers the full API and stays current when the API changes.

Q: Which AI clients can use SageMaker Feature Store Runtime through MCP?

MCP-compatible clients such as Claude, ChatGPT, Cursor, Codex or your own agents. They connect to one governed endpoint, so changing clients doesn’t mean rebuilding access.

Q: How do I control what AI agents can do in SageMaker Feature Store Runtime?

In the MCP Gateway, choose the tools each client may call. Allow reads, require human approval before sensitive writes and block the rest. Credentials stay in Mindflow and every call is logged.

Q: Can the same connection power automated workflows?

Yes. The same SageMaker Feature Store Runtime connector runs in Mindflow flows and AI··Agents, so one connection serves your AI clients and your automations.

Expose SageMaker Feature Store Runtime to Claude, ChatGPT, Cursor or your own agents as a governed MCP server, even if the vendor doesn’t ship one. Mindflow turns every API operation into an MCP tool and keeps the connector current when the API changes. The MCP Gateway sits between your AI clients and your data, with scoped access, human approval before sensitive writes and a record of every call.

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See the integration

operation

available

Complete and up-to-date endpoint coverage by Mindflow.

Other services from this vendor:

Other services from this portfolio:

operation

available

Complete and up-to-date endpoint coverage by Mindflow.

Other services from this vendor:

Other services from this portfolio:

operation

available

Complete and up-to-date endpoint coverage by Mindflow.

Other services from this vendor:

Other services from this portfolio:

Our customers scale automation with security built in.

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Tools exposed by this MCP server

Every SageMaker Feature Store Runtime operation, as an MCP tool

Each API operation becomes a tool your AI client can call. You decide which ones: allow reads, require approval before sensitive writes and block the rest. A few of the most used:

SageMaker Feature Store Runtime
SageMaker Feature Store Runtime
Delete a record from a feature group
Delete a record from a feature group
SageMaker Feature Store Runtime
SageMaker Feature Store Runtime
Get a record for online store serving
Get a record for online store serving
SageMaker Feature Store Runtime
SageMaker Feature Store Runtime
Put records into a feature group
Put records into a feature group
SageMaker Feature Store Runtime
SageMaker Feature Store Runtime
Retrieve a batch of records from a feature group
Retrieve a batch of records from a feature group

SageMaker Feature Store Runtime
Delete a record from a feature group
SageMaker Feature Store Runtime
Get a record for online store serving
SageMaker Feature Store Runtime
Put records into a feature group
SageMaker Feature Store Runtime
Retrieve a batch of records from a feature group

SageMaker Feature Store Runtime
SageMaker Feature Store Runtime
Retrieve a batch of records from a feature group
Retrieve a batch of records from a feature group
SageMaker Feature Store Runtime
SageMaker Feature Store Runtime
Put records into a feature group
Put records into a feature group
SageMaker Feature Store Runtime
SageMaker Feature Store Runtime
Get a record for online store serving
Get a record for online store serving
SageMaker Feature Store Runtime
SageMaker Feature Store Runtime
Delete a record from a feature group
Delete a record from a feature group

SageMaker Feature Store Runtime
Retrieve a batch of records from a feature group
SageMaker Feature Store Runtime
Put records into a feature group
SageMaker Feature Store Runtime
Get a record for online store serving
SageMaker Feature Store Runtime
Delete a record from a feature group

Connect SageMaker Feature Store Runtime to your AI client in three steps.

01 Connect the service

Add SageMaker Feature Store Runtime in Mindflow with its credentials. They stay in Mindflow and never reach the AI client.

02 Choose the tools

Pick the operations each AI client may call. Allow reads, require approval before sensitive writes and block the rest.

03 Connect your AI client

Point Claude, ChatGPT, Cursor or your own agent to your MCP Gateway endpoint, then check real calls in the audit log.

How the MCP Gateway governs every call

Use cases

What your AI agents can do with SageMaker Feature Store Runtime

AI clients

Mindflow

SageMaker Feature Store Runtime

→ Automate removal of outdated feature data from FeatureGroups to maintain data quality using DeleteRecord, ensuring models use accurate inputs. → Streamline real-time feature retrieval for online inference by automating GetRecord calls, enabling timely, model-ready data access. → Coordinate batch ingestion and retrieval of feature records through automated PutRecord and BatchGetRecord actions, supporting scalable machine learning pipelines.

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Amazon AWS Service Catalog App Registry

Amazon AWS Storage Gateway

Amazon Backup

Amazon Backup Storage

Every call goes through one governed endpoint.

Your AI clients get access. You keep control.

Every call to SageMaker Feature Store Runtime goes through the Mindflow MCP Gateway. The same policies apply to every AI client: role-based access by team and environment, scoped credentials that never reach the client, human approval before sensitive writes, and a log of every call you can export to your SIEM.

Discover the MCP Gateway

SageMaker Feature Store Runtime MCP server

Live

RBAC · SecOps

Scoped credentials

Audit log

Delete a record from a feature group

Allowed

Get a record for online store serving

Allowed

Put records into a feature group

Needs approval

Retrieve a batch of records from a feature group

Blocked

Every call logged · Export to SIEM

Questions about the SageMaker Feature Store Runtime MCP server

Clear answers before you connect an AI client.

What is the SageMaker Feature Store Runtime MCP server?

Do I need an official MCP server from the vendor?

Which AI clients can use SageMaker Feature Store Runtime through MCP?

How do I control what AI agents can do in SageMaker Feature Store Runtime?

Can the same connection power automated workflows?

Questions about the SageMaker Feature Store Runtime MCP server

Clear answers before you connect an AI client.

What is the SageMaker Feature Store Runtime MCP server?

Do I need an official MCP server from the vendor?

Which AI clients can use SageMaker Feature Store Runtime through MCP?

How do I control what AI agents can do in SageMaker Feature Store Runtime?

Can the same connection power automated workflows?

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Put this MCP server to work.

Bring one AI client and the tools it needs. We’ll show you the setup in Mindflow, from scoped access to the audit log.

Book a demo

Put this MCP server to work.

Bring one AI client and the tools it needs. We’ll show you the setup in Mindflow, from scoped access to the audit log.

Book a demo

Less busywork. More possibility.

Let your agents handle the routine. Make room for what comes next.

Let’s talk

Automation intelligence, delivered monthly.

Product releases, automation playbooks, and security research — straight to your inbox. No spam, unsubscribe anytime.

Less busywork. More possibility.

Let your agents handle the routine. Make room for what comes next.

Let’s talk

Automation intelligence, delivered monthly.

Product releases, automation playbooks, and security research — straight to your inbox. No spam, unsubscribe anytime.

Less busywork. More possibility.

Let your agents handle the routine. Make room for what comes next.

Let’s talk

Automation intelligence, delivered monthly.

Product releases, automation playbooks, and security research — straight to your inbox. No spam, unsubscribe anytime.

SOC Starter

Vulnerability Operations

DORA & NIS2

SOC Starter

SOC Starter

Vulnerability Operations

DORA & NIS2

SOC Starter

Every SageMaker Feature Store Runtime operation, as an MCP tool

Every SageMaker Feature Store Runtime operation, as an MCP tool

Connect SageMaker Feature Store Runtime to your AI client in three steps.

01

Connect the service

02

Choose the tools

03

Connect your AI client

What your AI agents can do with SageMaker Feature Store Runtime

What your AI agents can do with SageMaker Feature Store Runtime

More

More

Amazon

Amazon

AWS

AWS

MCP servers:

MCP servers:

Every call goes through one governed endpoint.

Every call goes through one governed endpoint.

Your AI clients get access. You keep control.

Your AI clients get access. You keep control.

Questions about the SageMaker Feature Store Runtime MCP server

Questions about the SageMaker Feature Store Runtime MCP server

Automation intelligence, delivered monthly.

Automation intelligence, delivered monthly.

Automation intelligence, delivered monthly.