This spike aims to investigate the feasibility and potential approaches for enhancing or automating the support for *Model Context Protocol (MCP)* servers within Podman. The MCP is a critical emerging standard for enabling Large Language Models (LLMs) and other AI agents to securely and contextually interact with external systems, tools, and data sources.

*Goals of this Spike:*

• *Understand Current State of MCP & Podman Interaction:*
• Document existing methods for using Podman with MCP servers (e.g., running MCP servers in Podman containers, Podman's role in providing context to MCP, manual setup steps).
• Identify current pain points, manual overhead, and limitations in the existing integration (e.g., complex networking, authentication challenges, lack of seamless tool exposure).
• Research how Podman can best serve as an environment for *hosting MCP servers* and how it can *consume MCP-provided tools/resources* for broader container orchestration.

• *Explore Automation Opportunities for MCP Integration:*
• Research potential mechanisms, Podman features, APIs, or external tools that could be leveraged to automate tasks related to MCP server interaction. This includes:
• Automating the deployment and management of MCP server containers with Podman.
• Exploring how Podman's networking capabilities can be optimized for MCP communication (e.g., `stdio` for local processes, HTTP/SSE for networked services).
• Investigating Podman's extensibility (e.g., Podman Desktop extensions, Podman's REST API, plugins) for building direct MCP integration points.
• Evaluating how Podman's existing features (e.g., volumes, secrets, Kubernetes YAML generation) can be better utilized for MCP server configurations.

• *Identify Key Integration Points & Use Cases:*
• Determine where improvements for MCP server support would be most impactful in Podman workflows (e.g., seamless exposure of containerized services as MCP tools, simplified context sharing for LLMs running in Podman, automated secure credential management for MCP servers).
• Brainstorm concrete use cases that would be enabled or significantly improved by better MCP-Podman integration (e.g., an LLM running in a Podman container interacting with a local file system via an MCP server also in Podman, or a Podman-managed application exposing its API as an MCP tool).

• *Evaluate Potential Solutions:*
• Brainstorm and briefly assess different approaches for achieving better MCP-Podman integration, such as:
• New Podman commands or options specifically for MCP.
• Enhanced documentation and best practices for common MCP-Podman scenarios.
• Development of external companion tools or orchestration scripts.

• *Propose Next Steps:*
• Based on the investigation, recommend concrete actions for future development, including potential epics or user stories for implementation. This might include outlining a high-level design or a proof-of-concept for a critical integration point.

*Deliverables:*

• A summary document (e.g., Confluence page, Google Doc) outlining the findings of the investigation, including current challenges, explored solutions, and identified opportunities.
• A brief presentation or discussion with relevant stakeholders (e.g., Podman core team, AI/LLM developers) to share findings and recommendations.
• A prioritized list of potential follow-up tasks (e.g., user stories, epics) for implementation, if deemed feasible and valuable.
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*Technical Details to Consider During Investigation:*

• *MCP Server APIs and Specifications:* Deep dive into the MCP specification (e.g., `tools/list`, `tools/call`, resource exposure, transport protocols like Stdio, HTTP + SSE).
• *Podman Extensibility:* How can Podman Desktop extensions or Podman's REST API be used to build MCP-aware functionality?
• *Containerization of MCP Servers:* Best practices for packaging and running MCP servers within Podman containers.
• *Authentication and Authorization:* How can Podman facilitate secure authentication between MCP clients/servers, potentially leveraging Podman secrets or native authentication mechanisms? OAuth 2.1 is a recommended best practice for MCP.
• *Network Configuration for MCP:* How to configure Podman networks (`podman network create`) to optimize communication for different MCP transport protocols and ensure secure isolation.
• *Context and Resource Sharing:* How can Podman help manage and expose contextual data (e.g., file systems, databases) to MCP servers running in containers?
• *Tool Discovery and Execution:* How can Podman assist in the discovery and invocation of MCP tools exposed by containerized services?
• *User Workflows:* Interview developers using Podman and LLMs to understand their current pain points and desired future state.