Docker Agent Deploy
DockerOfficialPublished by Docker
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- Tool integration
- Cloud and DevOps
- Apache-2.0
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides the procedures for exposing Docker Agents as network services, sharing them through OCI registries, and validating their performance through automated regression testing. It covers the lifecycle of an agent once the configuration is defined, including server modes like MCP, HTTP API, and chat, as well as the evaluation framework for ensuring consistent behavior across updates.
What it does
- Exposes agents as MCP, HTTP API, A2A, ACP, or OpenAI-compatible chat servers.
- Distributes agent configurations via OCI registries using push and pull commands.
- Automates agent quality checks using JSON-based evaluation sessions.
- Gates CI pipelines against regressions using baseline comparison and tolerance thresholds.
- Configures security and authentication for network-reachable agent endpoints.
- Manages isolated evaluation environments using container runtimes.
When to use it
- When you need to make an agent accessible to external clients or other agents.
- When you want to publish or share an agent configuration using standard container registry workflows.
- When you need to verify agent behavior after configuration changes to prevent regressions.
- When you need to integrate agent testing into a CI/CD pipeline.
Advantages
- Uses familiar OCI registry workflows for agent distribution.
- Provides deterministic assertion-based testing for reliable agent validation.
- Supports multiple server modes for flexible integration with various client types.
- Enables regression gating to maintain agent quality over time.
Usage examples
- “How do I turn my agent into an MCP server for Claude Desktop?”
- The agent can be served using 'docker agent serve mcp ./agent.yaml', which defaults to stdio transport suitable for local clients like Claude Desktop.
- “How can I publish my agent to Docker Hub?”
- Use 'docker agent share push ./agent.yaml docker.io/username/my-agent:latest' to distribute your agent configuration as an OCI artifact.
- “How do I test my agent in CI to ensure it doesn't regress?”
- Run 'docker agent eval ./agent.yaml --baseline results/baseline.json --regression-tolerance 0.05' to compare current performance against a known good state.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/docker/docker-agent-deploy/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip docker-agent-deploy.zip -d .agents/skills
Documentation by Docker
Docker Agent: Serving, Sharing, and Evaluating
Overview
This skill owns the integration surface of Docker Agent: making an agent
reachable by other software (docker agent serve), distributing it through
an OCI registry the way container images are distributed (docker agent share), and proving it still behaves after a change (docker agent eval).
It assumes the agent config already exists — see docker-agent-config for
authoring it, and docker-agent-run for interactive/local invocation.
When to use this skill
Activate this skill when:
The user wants an agent reachable over MCP, an OpenAI-compatible chat endpoint, a plain HTTP API, or A2A/ACP.
The user wants to publish an agent to Docker Hub (or any OCI registry) or pull one someone else published.
The user wants automated evaluations (regression tests) for an agent, or wants to gate CI on eval results.
Do not use this skill when
Do not use this skill when:
The task is authoring the agent.yaml itself (models, toolsets, sub_agents) — use
docker-agent-config.The task is running the agent interactively on a developer's machine, choosing
--safety/--sandbox, or aliases — usedocker-agent-run.
Core guidance
Serving an agent
Five server modes, each with its own default loopback listen address — never expose any of them beyond loopback without authentication:
Mode Default listen Auth flag Has --safety?serve mcp127.0.0.1:8081--auth-token(only with--http)Yes (only with --http)serve api127.0.0.1:8080--auth-tokenNo serve chat127.0.0.1:8083--api-key/--api-key-envYes serve a2a127.0.0.1:8082--auth-tokenYes serve acp(stdio only) n/a No docker agent serve mcp ./agent.yaml --http --listen 127.0.0.1:9090 --auth-token "$TOKEN"serve mcpdefaults to stdio transport (for local clients like Claude Desktop); pass--httponly when you need a network-reachable MCP endpoint, and set--auth-tokenwhenever you do.Binding any server flag to a non-loopback address without an auth token/key is refused;
--insecure-no-authexists to force it and must be treated as a deliberate, documented exception, never a default.serve mcp(with--http),serve chat, andserve a2aexpose--safety(strict/balanced/restricted/autonomous); Docker's docs state it defaults torestrictedfor these modes when unset.serve apiandserve acpexpose no--safetyflag at all. Never raise--safetytoautonomouson a network-reachable listener; if a served agent must approve more, preferbalancedand keep auth enabled.serve apiaccepts a directory instead of a single file: every.yaml/.yml/.hclin it is exposed under/api/agents. Use--session-workingdir-rootto confine session working directories when the server is reachable by more than one user.
Sharing agents via OCI registries
Push and pull agent configs the same way you push and pull images — same registry, same
docker loginauth:docker agent share push ./agent.yaml docker.io/username/my-agent:latest docker agent share pull docker.io/username/my-agent:latestinstruction_filecontents are inlined into the pushed artifact automatically, so a published agent stays self-contained — you do not need to bundle the referenced files separately.Pin
sub_agentsthat reference the pushed artifact to a digest (name@sha256:...) once published, to avoid a per-run registry lookup and to guarantee the exact config a consumer gets.Use
--forceonshare pullonly when you intend to overwrite a local copy that already exists; without it, an existing local config is left untouched.
Evaluating agents
Evals live in an
evals/directory next to the agent config by default; each eval is one JSON session file capturing a user message, the recorded tool calls, and anevalsobject with the scoring criteria.Create eval sessions from real conversations rather than hand-writing JSON: run the agent interactively, then use the
/evalslash command in the TUI to save the session, and edit inrelevance/size/assertionscriteria afterward.Four scoring dimensions: Tool Calls (F1 against the recorded sequence), Relevance (LLM-judge,
--judge-model, defaultanthropic/claude-opus-5), Size (S/M/L/XL response-length bucket), and Assertions (deterministic checks; see the complete assertion-type list inreferences/eval-format.md). Prefer assertions overrelevancewhen a check can be exact: they need no judge model and are deterministic, not approximation-prone.Evaluations run inside containers for isolation; a Docker-compatible runtime is required. Dedicated provider API keys (
ANTHROPIC_API_KEY/OPENAI_API_KEY) are forwarded automatically.GITHUB_TOKEN/GH_TOKENare not forwarded automatically (they're broad host credentials, not model keys) — pass them explicitly with-e GITHUB_TOKENwhen an agent's provider needs one (e.g.github-copilot).Gate CI on regressions, not on absolute scores, with
--baseline:docker agent eval ./agent.yaml --baseline results/2026-08-01-run.json --regression-tolerance 0.05A previously-passing eval that now fails always gates regardless of tolerance; cost changes are reported but never gate. A baseline or run with zero evaluations (e.g. an
--onlypattern matching nothing) is rejected rather than reported as passing.Use
--keep-containersplus your runtime'sexecto inspect a failed eval's container; the eval's.dbsession file holds the full conversation for offline debugging.
Verify
After changing a served agent's config, re-run its evals with the same explicit
--safetyvalue used in the deployment before restarting the listener — this catches an approval-policy regression before it reaches traffic. If a rollout must be rolled back, restore the prior config and safety flag; never restore an unauthenticated listener as a rollback shortcut.
Related skills
For writing or changing the underlying
agent.yaml, usedocker-agent-config.For local/interactive runs, safety-mode choice, and sandboxing, use
docker-agent-run.
References
references/eval-format.md— full eval session JSON schema and CLI flag table.references/sources.md— provenance of every rule in this skill.
Assets
assets/eval-session-example.json— a minimal eval session file to copy and adapt.
Checks
checks/verification.md— Verification runbook for serving, sharing, and evaluating an agent.
Files
- ATTRIBUTION.mdAdded by AutoGineer830 B
- LICENSELicence file added by AutoGineer11.1 KiB
- SKILL.md7.6 KiB
- agents/openai.yaml402 B
- assets/eval-session-example.json1.3 KiB
- checks/verification.md2.3 KiB
- references/eval-format.md2.6 KiB
- references/sources.md1.6 KiB
- skill.yaml923 B
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs an API key, Needs a command-line tool
The author says: Requires the docker-agent CLI plugin (Docker Desktop 4.63+, or standalone). `docker agent eval` additionally requires a Docker-compatible container runtime (Docker Desktop/Engine, or Podman via `--container-runtime`). Verified against docker-agent as shipped with Docker CLI 29.7.2.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Docker
- Publisher
- Docker (Official)
- Source
- docker/skills · skills/docker-agent-deploy · commit 9f04a05
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Docker.
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