What can mcp-server-docker do?

docker container command execution via mcp protocol, container discovery and enumeration, container lifecycle management (start/stop/restart), container file system access and inspection, container environment variable inspection and modification, container resource monitoring and stats collection, container log streaming and retrieval, container network inspection and connectivity testing

mcp-server-docker

MCP ServerFree

MCP server for executing commands in Docker containers

Open Source

/ 100

8 capabilities

Capabilities8 decomposed

docker container command execution via mcp protocol

Medium confidence

Executes arbitrary shell commands inside Docker containers through the Model Context Protocol, translating MCP tool calls into Docker CLI invocations with container ID/name targeting. The server acts as a bridge between LLM agents and Docker's exec API, handling command serialization, stream capture, and exit code propagation back to the client.

Solves for

Run diagnostic commands inside a running container without SSH or manual docker execLet an LLM agent perform infrastructure operations (file inspection, service restarts, log collection) directly in containerized environmentsExecute multi-step container workflows programmatically through an agent's tool-calling interfaceDebug container state and application behavior by running commands from an LLM chat interface

Best for

DevOps engineers building LLM-powered infrastructure automation agents

Teams using Claude or other MCP-compatible LLMs to manage containerized deployments

Developers prototyping intelligent container orchestration tools

Requires

Node.js 16+ (MCP server runtime)

Docker daemon running and accessible via /var/run/docker.sock or DOCKER_HOST environment variable

MCP-compatible client (Claude, custom agent framework, etc.)

Limitations

Requires Docker daemon access on the host running the MCP server — no remote Docker support without additional networking setup

No built-in sandboxing or command whitelisting — any MCP client can execute arbitrary commands in any accessible container

Command execution is synchronous and blocking — long-running operations will timeout if MCP client has strict timeout policies

What makes it unique

Implements Docker command execution as a first-class MCP tool, allowing LLM agents to directly invoke container operations without requiring custom API wrappers or shell script intermediaries. Uses Docker's native exec API for in-container execution rather than SSH or container restart patterns.

vs alternatives

Simpler than building custom Docker API clients or REST wrappers because it leverages MCP's standardized tool-calling protocol, making it immediately compatible with any MCP-aware LLM without additional integration code.

container discovery and enumeration

Medium confidence

Provides MCP tools to list and inspect available Docker containers (running and stopped), exposing container metadata including IDs, names, images, status, and port mappings. This enables LLM agents to discover which containers are available before targeting them for command execution, implemented via Docker API queries wrapped in MCP tool definitions.

Solves for

Discover which containers are running in the Docker environment before executing commandsGet container metadata (image, ports, environment) to inform which container to target for operationsMonitor container state changes and report status to an LLM agent for decision-makingBuild dynamic workflows that adapt based on available containers

Best for

Agents managing multi-container deployments where container availability varies

Infrastructure monitoring and troubleshooting workflows

Teams needing dynamic container targeting rather than hardcoded container names

Requires

Docker daemon running and accessible

Docker API permissions for the MCP server process

Limitations

Returns only containers accessible to the Docker daemon user — no cross-daemon or remote Docker enumeration without explicit configuration

Metadata is point-in-time snapshot; no streaming updates or event subscriptions for container lifecycle changes

Large deployments with hundreds of containers may return verbose output that exceeds MCP context limits

What makes it unique

Exposes Docker container enumeration as MCP tools rather than requiring agents to shell out to docker ps or parse CLI output, providing structured, type-safe access to container metadata within the MCP protocol.

vs alternatives

More reliable than parsing docker CLI output because it uses Docker's native API directly, and more agent-friendly than requiring custom shell commands since it returns structured data natively compatible with LLM function calling.

container lifecycle management (start/stop/restart)

Medium confidence

Provides MCP tools to control Docker container lifecycle operations (start, stop, restart, remove) by translating MCP tool calls into Docker API state-change operations. The server handles idempotency concerns (e.g., stopping an already-stopped container) and propagates operation results back to the MCP client.

Solves for

Start or stop containers as part of an automated deployment or maintenance workflowRestart a misbehaving service container without manual interventionClean up stopped containers or remove containers as part of infrastructure teardownImplement self-healing workflows where an agent restarts containers based on health checks

Best for

DevOps automation agents managing container deployments

Self-healing infrastructure systems that respond to container failures

Teams automating container lifecycle as part of CI/CD or infrastructure-as-code workflows

Requires

Docker daemon running and accessible

Docker API permissions to modify container state (requires elevated privileges on some systems)

Limitations

No graceful shutdown timeout configuration — stop operations use Docker's default timeout (10s) before force-killing

No transaction semantics — if a multi-container operation fails partway through, no automatic rollback

Restart operations are simple stop-then-start; no support for rolling restarts or blue-green deployment patterns

What makes it unique

Wraps Docker container state transitions as MCP tools, allowing LLM agents to orchestrate container lifecycle without needing to understand Docker CLI syntax or API details. Handles operation idempotency and error propagation transparently.

vs alternatives

More declarative and agent-friendly than shell commands because it exposes lifecycle operations as typed MCP tools, and safer than direct Docker API calls because the MCP server can enforce policies or logging before delegating to Docker.

container file system access and inspection

Medium confidence

Provides MCP tools to read, write, and inspect files within running containers by translating file operations into docker cp and docker exec commands. The server handles path resolution, permission checking, and content encoding (text vs binary) to enable agents to inspect logs, configuration files, and application state without entering the container interactively.

Solves for

Read application logs or configuration files from inside a container for debuggingInspect container file system state to diagnose application issuesWrite configuration or script files into a container for dynamic configurationExtract artifacts (dumps, reports) from a container to the host for analysis

Best for

Debugging workflows where agents need to inspect container internals

Log aggregation and analysis agents that pull logs from multiple containers

Configuration management systems that need to modify container files dynamically

Requires

Docker daemon running and accessible

Container must be running (docker cp requires container to exist, but docker exec requires it to be running)

Limitations

File operations are limited to paths accessible by the container's user — no privilege escalation within the container

Large file transfers may be slow or timeout depending on MCP client timeout policies

Binary file handling is limited — encoding/decoding adds overhead and may corrupt binary data

What makes it unique

Abstracts container file system access through MCP tools, allowing agents to read/write files without understanding docker cp syntax or managing temporary files on the host. Handles encoding and path resolution transparently.

vs alternatives

More convenient than manual docker cp commands because it's integrated into the MCP tool interface, and safer than mounting host volumes because it operates through Docker's native file copy mechanism with built-in isolation.

container environment variable inspection and modification

Medium confidence

Provides MCP tools to read and modify environment variables within running containers by inspecting container configuration and using docker exec to set variables dynamically. The server exposes container environment metadata and allows agents to update variables without restarting the container (for variables read at runtime) or to prepare environment changes for restart.

Solves for

Inspect what environment variables are set in a container for debugging configuration issuesDynamically update application configuration via environment variables without container restartPrepare environment variable changes for a container restartAudit environment variable usage across multiple containers

Best for

Configuration management agents that adjust application settings dynamically

Debugging workflows where environment configuration is suspected as the issue

Teams using environment-based configuration (12-factor app pattern)

Requires

Docker daemon running and accessible

Container must be running for dynamic variable modification

Limitations

Environment variables set at container start time (via docker run -e or Dockerfile ENV) cannot be modified without restart

Variables set dynamically via docker exec are lost on container restart unless persisted elsewhere

No validation of variable format or values — agent is responsible for ensuring valid configuration

What makes it unique

Exposes container environment inspection and modification as MCP tools, allowing agents to manage application configuration without understanding Docker's environment variable scoping or restart semantics. Abstracts the difference between build-time and runtime environment variables.

vs alternatives

More agent-friendly than manual docker inspect and docker exec commands because it provides structured access to environment data, and more flexible than static configuration files because it allows runtime modification without container restart.

container resource monitoring and stats collection

Medium confidence

Provides MCP tools to query Docker container resource usage statistics (CPU, memory, network I/O, block I/O) by polling the Docker stats API. The server translates real-time container metrics into structured data that agents can use for monitoring, alerting, or auto-scaling decisions.

Solves for

Monitor container resource consumption to detect performance issues or resource leaksCollect metrics for alerting workflows (e.g., restart container if memory exceeds threshold)Implement auto-scaling logic based on container resource usageAudit resource usage across multiple containers for capacity planning

Best for

Infrastructure monitoring agents that need real-time container metrics

Auto-scaling systems that make decisions based on resource consumption

Debugging workflows investigating container performance issues

Requires

Docker daemon running and accessible

Container must be running to collect stats

Limitations

Stats are point-in-time snapshots; no historical data or time-series aggregation — agent must implement its own metrics storage

Docker stats API has ~1-2 second latency; not suitable for sub-second monitoring

Metrics are relative to the container's cgroup limits, not absolute host resources — interpretation depends on container resource constraints

What makes it unique

Exposes Docker container resource metrics as MCP tools, allowing agents to make monitoring and scaling decisions without parsing docker stats CLI output or implementing custom Docker API polling. Returns structured, type-safe metric data.

vs alternatives

More agent-friendly than docker stats CLI because it returns structured JSON, and simpler than integrating Prometheus or other monitoring stacks because it provides direct access to Docker's native metrics without external infrastructure.

container log streaming and retrieval

Medium confidence

Provides MCP tools to retrieve container logs (stdout/stderr) by querying Docker's log driver, with support for filtering by timestamp, tail count, and follow mode. The server handles log encoding, stream buffering, and pagination to allow agents to inspect application output for debugging or log aggregation.

Solves for

Retrieve recent logs from a container to diagnose application failures or errorsStream logs in real-time to an agent for live monitoring or incident responseAggregate logs from multiple containers for centralized analysisSearch logs for specific error patterns or events

Best for

Debugging agents that need to inspect application logs

Log aggregation and analysis workflows

Incident response systems that collect logs for root cause analysis

Requires

Docker daemon running and accessible

Container must have logs available (depends on log driver configuration)

Limitations

Log retrieval depends on Docker's configured log driver (json-file, syslog, etc.); some drivers don't support log retrieval

Large logs may exceed MCP message size limits; pagination/tail filtering is required for large containers

Log timestamps are container-relative; no automatic timezone conversion or correlation with host time

What makes it unique

Wraps Docker log retrieval as MCP tools with filtering and pagination support, allowing agents to access container logs without understanding Docker's log driver architecture or managing log file paths. Handles encoding and stream buffering transparently.

vs alternatives

More convenient than docker logs CLI because it's integrated into the MCP tool interface with structured filtering, and more flexible than mounting log volumes because it works with any Docker log driver and doesn't require host-level file access.

container network inspection and connectivity testing

Medium confidence

Provides MCP tools to inspect container network configuration (IP addresses, port mappings, network connections) and test connectivity by executing network diagnostic commands (ping, curl, netstat) inside containers. The server translates network queries into docker exec invocations, allowing agents to diagnose network issues without manual container access.

Solves for

Inspect container IP addresses and port mappings to verify network configurationTest connectivity between containers or to external servicesDiagnose network issues (DNS resolution, routing, firewall) by running diagnostic commandsVerify that a service is listening on expected ports before routing traffic to it

Best for

Debugging agents troubleshooting container networking issues

Health check systems that verify service connectivity

Network configuration validation workflows

Requires

Docker daemon running and accessible

Container must be running and have network diagnostic tools installed

Limitations

Network diagnostics depend on tools available in the container image (ping, curl, netstat, etc.); minimal images may lack these tools

Connectivity tests are from the container's perspective; results may differ from host or external perspectives

No built-in DNS resolution caching or retry logic — agent must handle transient network failures

What makes it unique

Combines container network metadata inspection with in-container diagnostic command execution as MCP tools, allowing agents to diagnose network issues comprehensively without manual container access or understanding Docker's network driver architecture.

vs alternatives

More comprehensive than docker inspect alone because it includes connectivity testing, and more agent-friendly than manual docker exec commands because it provides structured results and handles common diagnostic patterns.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Related Artifactssharing capabilities

Artifacts that share capabilities with mcp-server-docker, ranked by overlap. Discovered automatically through the match graph.

Repository26

ToolHive

** - A lightweight utility designed to simplify the deployment and management of MCP servers, ensuring ease of use, consistency, and security through containerization by **[StacklokLabs](https://github.com/StacklokLabs)**

cli-driven mcp server lifecycle management (run, list, stop, remove)mcp server containerized deployment with oci standards

2 shared capabilities

MCP Server46

Docker MCP Server

Manage Docker containers, images, and volumes via MCP.

container lifecycle operations (run, stop, restart, remove) with environment and port binding configurationcommand execution inside running containers with stdin/stdout capture

2 shared capabilities

MCP Server38

datagouv-mcp

Official data.gouv.fr Model Context Protocol (MCP) server that allows AI chatbots to search, explore, and analyze datasets from the French national Open Data platform, directly through conversation.

docker containerization and cloud-ready deployment

1 shared capability

MCP Server25

any-chat-completions-mcp

** - Chat with any other OpenAI SDK Compatible Chat Completions API, like Perplexity, Groq, xAI and more

docker containerized deployment

1 shared capability

MCP Server24

AgentQL

** - Enable AI agents to get structured data from unstructured web with [AgentQL](https://www.agentql.com/).

docker containerization and orchestration support

1 shared capability

MCP Server41

exa-mcp-server

Exa MCP for web search and web crawling!

docker containerization for portable deployment

1 shared capability

Best For

✓DevOps engineers building LLM-powered infrastructure automation agents
✓Teams using Claude or other MCP-compatible LLMs to manage containerized deployments
✓Developers prototyping intelligent container orchestration tools
✓Agents managing multi-container deployments where container availability varies
✓Infrastructure monitoring and troubleshooting workflows
✓Teams needing dynamic container targeting rather than hardcoded container names
✓DevOps automation agents managing container deployments
✓Self-healing infrastructure systems that respond to container failures

Known Limitations

⚠Requires Docker daemon access on the host running the MCP server — no remote Docker support without additional networking setup
⚠No built-in sandboxing or command whitelisting — any MCP client can execute arbitrary commands in any accessible container
⚠Command execution is synchronous and blocking — long-running operations will timeout if MCP client has strict timeout policies
⚠No persistent session state — each command invocation is isolated; multi-step workflows require explicit state management by the LLM agent
⚠Returns only containers accessible to the Docker daemon user — no cross-daemon or remote Docker enumeration without explicit configuration
⚠Metadata is point-in-time snapshot; no streaming updates or event subscriptions for container lifecycle changes

Requirements

Node.js 16+ (MCP server runtime)Docker daemon running and accessible via /var/run/docker.sock or DOCKER_HOST environment variableMCP-compatible client (Claude, custom agent framework, etc.)Appropriate Docker permissions for the user running the MCP server processDocker daemon running and accessibleDocker API permissions for the MCP server processDocker API permissions to modify container state (requires elevated privileges on some systems)Container must be running (docker cp requires container to exist, but docker exec requires it to be running)

Input / Output

Accepts: container identifier (name or ID), shell command string, optional working directory path, optional filter parameters (status, label, etc.), operation type (start, stop, restart, remove), container identifier, file path within container, file content (for write operations), environment variable name and value (for modification), optional filters (tail count, since timestamp, until timestamp, follow flag), target host/IP for connectivity testing, port number (optional)

Produces: stdout text stream, stderr text stream, exit code (integer), structured JSON array of container objects, container metadata (ID, name, image, status, ports), operation status (success/failure), error message if operation failed, file content as text or base64-encoded binary, file metadata (size, permissions, modification time), structured map of environment variables, confirmation of variable modification, structured metrics object (CPU %, memory usage, network I/O, block I/O), log text (stdout/stderr combined or separated), log metadata (timestamps, stream source), network configuration (IP addresses, port mappings), connectivity test results (success/failure, latency), diagnostic command output (netstat, route, etc.)

UnfragileRank

Adoption15%(30% weight)

Quality17%(25% weight)

Ecosystem45%(25% weight)

Match Graph10%(15% weight)

Freshness75%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: MCP Server

8 capabilities

Visit mcp-server-docker→

Package Details

npm

Registry

1.0.0

Version

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MCP server for executing commands in Docker containers

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Capabilities8 decomposed

docker container command execution via mcp protocol

Medium confidence

Solves for

Best for

DevOps engineers building LLM-powered infrastructure automation agents

Teams using Claude or other MCP-compatible LLMs to manage containerized deployments

Developers prototyping intelligent container orchestration tools

Requires

Node.js 16+ (MCP server runtime)

Docker daemon running and accessible via /var/run/docker.sock or DOCKER_HOST environment variable

MCP-compatible client (Claude, custom agent framework, etc.)

Limitations

Requires Docker daemon access on the host running the MCP server — no remote Docker support without additional networking setup

No built-in sandboxing or command whitelisting — any MCP client can execute arbitrary commands in any accessible container

Command execution is synchronous and blocking — long-running operations will timeout if MCP client has strict timeout policies

What makes it unique

vs alternatives

container discovery and enumeration

Medium confidence

Solves for

Best for

Agents managing multi-container deployments where container availability varies

Infrastructure monitoring and troubleshooting workflows

Teams needing dynamic container targeting rather than hardcoded container names

Requires

Docker daemon running and accessible

Docker API permissions for the MCP server process

Limitations

Returns only containers accessible to the Docker daemon user — no cross-daemon or remote Docker enumeration without explicit configuration

Metadata is point-in-time snapshot; no streaming updates or event subscriptions for container lifecycle changes

Large deployments with hundreds of containers may return verbose output that exceeds MCP context limits

What makes it unique

vs alternatives

container lifecycle management (start/stop/restart)

Medium confidence

Solves for

Best for

DevOps automation agents managing container deployments

Self-healing infrastructure systems that respond to container failures

Teams automating container lifecycle as part of CI/CD or infrastructure-as-code workflows

Requires

Docker daemon running and accessible

Docker API permissions to modify container state (requires elevated privileges on some systems)

Limitations

No graceful shutdown timeout configuration — stop operations use Docker's default timeout (10s) before force-killing

No transaction semantics — if a multi-container operation fails partway through, no automatic rollback

Restart operations are simple stop-then-start; no support for rolling restarts or blue-green deployment patterns

What makes it unique

vs alternatives

container file system access and inspection

Medium confidence

Solves for

Best for

Debugging workflows where agents need to inspect container internals

Log aggregation and analysis agents that pull logs from multiple containers

Configuration management systems that need to modify container files dynamically

Requires

Docker daemon running and accessible

Container must be running (docker cp requires container to exist, but docker exec requires it to be running)

Limitations

File operations are limited to paths accessible by the container's user — no privilege escalation within the container

Large file transfers may be slow or timeout depending on MCP client timeout policies

Binary file handling is limited — encoding/decoding adds overhead and may corrupt binary data

What makes it unique

vs alternatives

container environment variable inspection and modification

Medium confidence

Solves for

Best for

Configuration management agents that adjust application settings dynamically

Debugging workflows where environment configuration is suspected as the issue

Teams using environment-based configuration (12-factor app pattern)

Requires

Docker daemon running and accessible

Container must be running for dynamic variable modification

Limitations

Environment variables set at container start time (via docker run -e or Dockerfile ENV) cannot be modified without restart

Variables set dynamically via docker exec are lost on container restart unless persisted elsewhere

No validation of variable format or values — agent is responsible for ensuring valid configuration

What makes it unique

vs alternatives

container resource monitoring and stats collection

Medium confidence

Solves for

Best for

Infrastructure monitoring agents that need real-time container metrics

Auto-scaling systems that make decisions based on resource consumption

Debugging workflows investigating container performance issues

Requires

Docker daemon running and accessible

Container must be running to collect stats

Limitations

Stats are point-in-time snapshots; no historical data or time-series aggregation — agent must implement its own metrics storage

Docker stats API has ~1-2 second latency; not suitable for sub-second monitoring

Metrics are relative to the container's cgroup limits, not absolute host resources — interpretation depends on container resource constraints

What makes it unique

vs alternatives

container log streaming and retrieval

Medium confidence

Solves for

Best for

Debugging agents that need to inspect application logs

Log aggregation and analysis workflows

Incident response systems that collect logs for root cause analysis

Requires

Docker daemon running and accessible

Container must have logs available (depends on log driver configuration)

Limitations

Log retrieval depends on Docker's configured log driver (json-file, syslog, etc.); some drivers don't support log retrieval

Large logs may exceed MCP message size limits; pagination/tail filtering is required for large containers

Log timestamps are container-relative; no automatic timezone conversion or correlation with host time

What makes it unique

vs alternatives

container network inspection and connectivity testing

Medium confidence

Solves for

Best for

Debugging agents troubleshooting container networking issues

Health check systems that verify service connectivity

Network configuration validation workflows

Requires

Docker daemon running and accessible

Container must be running and have network diagnostic tools installed

Limitations

Network diagnostics depend on tools available in the container image (ping, curl, netstat, etc.); minimal images may lack these tools

Connectivity tests are from the container's perspective; results may differ from host or external perspectives

No built-in DNS resolution caching or retry logic — agent must handle transient network failures

What makes it unique

vs alternatives

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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mcp-server-docker

Capabilities8 decomposed

docker container command execution via mcp protocol

container discovery and enumeration

container lifecycle management (start/stop/restart)

container file system access and inspection

container environment variable inspection and modification

container resource monitoring and stats collection

container log streaming and retrieval

container network inspection and connectivity testing

Related Artifactssharing capabilities

ToolHive

Docker MCP Server

datagouv-mcp

any-chat-completions-mcp

AgentQL

exa-mcp-server

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to mcp-server-docker

Are you the builder of mcp-server-docker?

Get the weekly brief

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mcp-server-docker

Capabilities8 decomposed

docker container command execution via mcp protocol

container discovery and enumeration

container lifecycle management (start/stop/restart)

container file system access and inspection

container environment variable inspection and modification

container resource monitoring and stats collection

container log streaming and retrieval

container network inspection and connectivity testing

Related Artifactssharing capabilities

ToolHive

Docker MCP Server

datagouv-mcp

any-chat-completions-mcp

AgentQL

exa-mcp-server

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to mcp-server-docker

Are you the builder of mcp-server-docker?

Get the weekly brief

Data Sources