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Feature
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Resolution: Unresolved
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Major
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None
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False
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False
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Not Selected
Feature Overview
This feature involves creating a prototype of a Model Context Protocol (MCP) server that exposes Red Hat Advanced Cluster Management (ACM) Search data and capabilities to external AI models and agents. This will enable natural language queries and AI-driven workflows for managing Kubernetes clusters. This initial version will be a Developer Preview to gather feedback and validate the architectural approach.
Goals
This Section: Provide high-level goal statement, providing user context
and expected user outcome(s) for this feature
- Create a functional MCP server prototype that can be consumed by an MCP client (e.g., an LLM).
- Expose key Search data as structured resources and API tools via the MCP.
- Validate the feasibility, performance, and security of using the MCP to enable AI-driven interactions with ACM Search.
- Gather developer and user feedback on the prototype to inform the future direction of AI-enabled features in ACM.
Requirements
This Section: A list of specific needs or objectives that a Feature must
deliver to satisfy the Feature.. Some requirements will be flagged as MVP.
If an MVP gets shifted, the feature shifts. If a non MVP requirement slips,
it does not shift the feature.
Requirement | Notes | isMvp? |
---|---|---|
The MCP server prototype MUST be able to connect to the ACM Search API to retrieve data. | YES | |
The prototype MUST expose at least one "tool" that an LLM can invoke (e.g., a tool for searching for clusters or resources by name). | YES | |
The prototype MUST define and expose a schema that describes the available resources (e.g., Cluster, Pod, Application). | NO | |
The prototype MUST be able to return structured data in a format consumable by the LLM. | YES | |
CI - MUST be running successfully with test automation | This is a requirement for ALL features. |
YES |
Release Technical Enablement | Provide necessary release enablement details and documents. |
YES |
(Optional) Use Cases
This Section:
Main success scenarios - high-level user stories:
- As an AI assistant user, I want to be able to ask "How many clusters are in my environment?" and receive a correct answer from the ACM Search data.
- As a developer using an AI-integrated IDE, I want to ask "Show me all pods in the acm-monitoring namespace" and have the Search MCP server retrieve that data.
- As an ACM administrator, I want to use natural language commands to find resources that match specific criteria, such as "Find all non-compliant policies in the production cluster."
Alternate flow/scenarios - high-level user stories:
- If a user's query is ambiguous, the MCP server should provide the LLM with sufficient context to ask for clarification.
- The prototype should handle basic security considerations, such as not exposing unauthorized data, even to the LLM.
Questions to answer
- Engineering will need to work out the best approach for retrieving the data from Search; whether its via our APIs (GraphQL endpoint), direct database querying, etc.
Out of Scope
- This feature is a prototype and is NOT a production-ready, highly available service.
- Implementing a full-fledged chat UI or agent on the client-side. This feature focuses only on the MCP server prototype.
- We will use existing client-side chat interfaces such as Claude Code/Desktop to validate.
- This work will target an integration with OpenShift Lightspeed at a later time.
- Complex multi-step actions or "agents" that chain multiple tool calls together.
- Writing data to the database (mutations). This will be a read-only prototype.
- Implementing a long-term security model; the prototype will use a basic proof-of-concept authentication and authorization method.
Background, and strategic fit
This Section: What does the person writing code, testing, documenting
need to know? What context can be provided to frame this feature?
Assumptions
- ...
Customer Considerations
- ...
Documentation Considerations
Questions to be addressed:
- What educational or reference material (docs) is required to support this
product feature? For users/admins? Other functions (security officers, etc)? - Does this feature have a doc impact?
- New Content, Updates to existing content, Release Note, or No Doc Impact
- If unsure and no Technical Writer is available, please contact Content
Strategy. - What concepts do customers need to understand to be successful in
[action]? - How do we expect customers will use the feature? For what purpose(s)?
- What reference material might a customer want/need to complete [action]?
- Is there source material that can be used as reference for the Technical
Writer in writing the content? If yes, please link if available. - What is the doc impact (New Content, Updates to existing content, or
Release Note)?
- clones
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ACM-21064 AI-Enabled RHACM Search via MCP Server (Dev Preview)
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- In Progress
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- depends on
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ACM-19061 Deliver ACM MCP Server with the toolset
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- New
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ACM-23306 MCP Server for search based on DB access
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- In Progress
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- is cloned by
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ACM-23643 AI-Enabled RHACM Search via MCP Server (GA)
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- New
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- is duplicated by
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ACM-19924 Integrate ACM Search with AI for natural language search
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- Closed
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- relates to
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ACM-23642 AI-Enabled Policy-based Governance via MCP Server (GA)
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- New
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ACM-23630 AI-Enabled Policy-based Governance via MCP Server (Tech Preview)
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- New
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