Podman▌
by manusa
Integrate with Podman for seamless container creation, management, and orchestration in automated DevOps and microservic
Integrates with Podman's API to enable container creation, management, and orchestration for automated DevOps workflows and microservices architecture deployment.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / DevOps engineers managing container workflows
- / Developers testing containerized applications
- / System administrators orchestrating microservices
- / CI/CD pipeline automation
capabilities
- / Create and start containers
- / Build container images from Dockerfiles
- / Monitor container status and logs
- / Manage container networks and volumes
- / Pull and push container images
- / Execute commands inside running containers
what it does
Provides direct API access to Podman for container management through conversational interfaces. Enables creation, monitoring, and orchestration of containers and images without switching between tools.
about
Podman is a community-built MCP server published by manusa that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate with Podman for seamless container creation, management, and orchestration in automated DevOps and microservic It is categorized under developer tools.
how to install
You can install Podman in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
Apache-2.0
Podman is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Podman MCP Server
✨ Features | 🚀 Getting Started | 📚 Documentation | 🎥 Demos | ⚙️ Configuration | 🛠️ Tools | 🧑💻 Development
✨ Features <a id="features"></a>
A powerful and flexible MCP server for container runtimes supporting Podman and Docker.
🚀 Getting Started <a id="getting-started"></a>
Claude Desktop
Using npx
If you have npm installed, this is the fastest way to get started with podman-mcp-server on Claude Desktop.
Open your claude_desktop_config.json and add the mcp server to the list of mcpServers:
{
"mcpServers": {
"podman": {
"command": "npx",
"args": [
"-y",
"podman-mcp-server@latest"
]
}
}
}
VS Code / VS Code Insiders
Install the Podman MCP server by clicking one of the following links:
<img src="https://img.shields.io/badge/VS_Code-VS_Code?style=flat-square&label=Install%20Server&color=0098FF" alt="Install in VS Code"> <img alt="Install in VS Code Insiders" src="https://img.shields.io/badge/VS_Code_Insiders-VS_Code_Insiders?style=flat-square&label=Install%20Server&color=24bfa5">
Alternatively, you can install the extension manually by running the following command:
# For VS Code
code --add-mcp '{"name":"podman","command":"npx","args":["-y","podman-mcp-server@latest"]}'
# For VS Code Insiders
code-insiders --add-mcp '{"name":"podman","command":"npx","args":["-y","podman-mcp-server@latest"]}'
Goose CLI
Goose CLI is the easiest (and cheapest) way to get rolling with artificial intelligence (AI) agents.
Using npm
If you have npm installed, this is the fastest way to get started with podman-mcp-server.
Open your goose config.yaml and add the mcp server to the list of mcpServers:
extensions:
podman:
command: npx
args:
- -y
- podman-mcp-server@latest
📚 Documentation <a id="documentation"></a>
For detailed setup guides, configuration reference, and feature specifications, see the Documentation.
🎥 Demos <a id="demos"></a>
⚙️ Configuration <a id="configuration"></a>
The Podman MCP server can be configured using command line (CLI) arguments.
You can run the CLI executable either by using npx or by downloading the latest release binary.
# Run the Podman MCP server using npx (in case you have npm installed)
npx podman-mcp-server@latest --help
# Run the Podman MCP server using the latest release binary
./podman-mcp-server --help
Configuration Options
| Option | Description |
|---|---|
--port, -p | Starts the MCP server in HTTP mode with Streamable HTTP at /mcp and SSE at /sse endpoints. |
--output-format, -o | Output format for list commands: text (default, human-readable table) or json. |
--podman-impl | Podman implementation to use. Auto-detects if not specified. |
--sse-port | Deprecated. Use --port instead. Starts the MCP server in SSE-only mode. |
--sse-base-url | Deprecated. SSE public base URL to use when sending the endpoint message. |
Transport Modes
The server supports multiple transport modes:
- STDIO mode (default) - Communicates via standard input/output
- HTTP mode (
--port) - Modern HTTP transport with both Streamable HTTP and SSE endpoints - SSE-only mode (
--sse-port) - Legacy Server-Sent Events transport (deprecated)
# Start HTTP server on port 8080 (Streamable HTTP at /mcp and SSE at /sse)
podman-mcp-server --port 8080
# Legacy SSE-only server on port 8080 (deprecated, use --port instead)
podman-mcp-server --sse-port 8080
Podman Implementations
The server supports multiple Podman backend implementations:
| Implementation | Description | Priority |
|---|---|---|
api | Podman REST API via Unix socket | 100 (preferred) |
cli | Podman/Docker CLI wrapper | 50 (fallback) |
By default, the server auto-detects the best available implementation.
The api implementation is preferred when a Podman socket is available, otherwise the cli implementation is used as a fallback.
Use the --podman-impl flag to force a specific implementation:
# Force CLI implementation
podman-mcp-server --podman-impl=cli
# Force API implementation (requires Podman socket)
podman-mcp-server --podman-impl=api
The api implementation communicates directly with the Podman REST API via Unix socket, while the cli implementation shells out to the podman or docker binary.
🛠️ Tools <a id="tools"></a>
<!-- AVAILABLE-TOOLS-START --> <details> <summary>Container</summary>-
container_inspect - Displays the low-level information and configuration of a Docker or Podman container with the specified container ID or name
name(string) (required) - Docker or Podman container ID or name to display the information
-
container_list - Prints out information about the running Docker or Podman containers
-
container_logs - Displays the logs of a Docker or Podman container with the specified container ID or name
name(string) (required) - Docker or Podman container ID or name to display the logs
-
container_remove - Removes a Docker or Podman container with the specified container ID or name (rm)
name(string) (required) - Docker or Podman container ID or name to remove
-
container_run - Runs a Docker or Podman container with the specified image name
environment(array) - Environment variables to set in the container. Format: <key>=<value>. Example: FOO=bar. (Optional, add only to set environment variables)imageName(string) (required) - Docker or Podman container image name to runports(array) - Port mappings to expose on the host. Format: <hostPort>:<containerPort>. Example: 8080:80. (Optional, add only to expose ports)
-
container_stop - Stops a Docker or Podman running container with the specified container ID or name
name(string) (required) - Docker or Podman container ID or name to stop
-
image_build - Build a Docker or Podman image from a Dockerfile, Podmanfile, or Containerfile
containerFile(string) (required) - The absolute path to the Dockerfile, Podmanfile, or Containerfile to build the image fromimageName(string) - Specifies the name which is assigned to the resulting image if the build process completes successfully (--tag, -t)
-
image_list - List the Docker or Podman images on the local machine
-
image_pull - Copies (pulls) a Docker or Podman container image from a registry onto the local machine storage
imageName(string) (required) - Docker or Podman container image name to pull
-
image_push - Pushes a Docker or Podman container image, manifest list or image index from local machine storage to a registry
imageName(string) (required) - Docker or Podman container image name to push
-
image_remove - Removes a Docker or Podman image from the local machine storage
imageName(string) (required) - Docker or Podman container image name to remove
- network_list - List all the available Docker or Podman networks
- volume_list - List all the available Docker or Podman volumes
🧑💻 Development <a id="development"></a>
Running with mcp-inspector
Compile the project and run the Podman MCP server with mcp-inspector to inspect the MCP server.
# Compile the project
make build
# Run the Podman MCP server with mcp-inspector
npx @modelcontextprotocol/inspector@latest $(pwd)/podman-mcp-server
mcp-name: io.github.manusa/podman-mcp-server
FAQ
- What is the Podman MCP server?
- Podman is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Podman?
- This profile displays 65 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.6★★★★★65 reviews- ★★★★★Sakura Taylor· Dec 28, 2024
We wired Podman into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Pratham Ware· Dec 24, 2024
Podman has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Jin Garcia· Dec 24, 2024
We evaluated Podman against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Hana Abbas· Dec 24, 2024
I recommend Podman for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Hiroshi Martinez· Dec 20, 2024
Podman reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Sakura Bansal· Dec 20, 2024
According to our notes, Podman benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Jin Martin· Dec 16, 2024
Podman is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Hiroshi Perez· Nov 19, 2024
Strong directory entry: Podman surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Sakshi Patil· Nov 15, 2024
According to our notes, Podman benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Arya Rahman· Nov 15, 2024
Podman is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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