Official agent skill

Amazon Workspaces Agent Access

by aws in aws/agent-toolkit-for-aws

Connects AI agents to remote Windows desktop applications on Amazon WorkSpaces Applications (AppStream 2.0) through the managed Agent Access MCP server, and guides reliable desktop automation.

OfficialApache-2.0Auto-check passedProductivity & Automation

Install Amazon Workspaces Agent Access

skills CLI
$ npx skills add aws/agent-toolkit-for-aws --skill amazon-workspaces-agent-access -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aws/agent-toolkit-for-aws amazon-workspaces-agent-access --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/specialized-skills/end-user-computing-skills/amazon-workspaces-agent-access .claude/skills/amazon-workspaces-agent-access && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
amazon-workspaces-agent-access
GitHub stars
2.8k
Token cost
~2.7k tokens
SKILL.md length
1,084 words
Files
9 (incl. references)
Skills in repo
138
Repo updated
First seen
Licence
Apache-2.0

At a glance

Connects AI agents to remote Windows desktop applications on Amazon WorkSpaces Applications (AppStream 2.0) through the managed Agent Access MCP server, and guides reliable desktop automation.

  • Debugging an agent that drives a remote Windows desktop
  • SKILL.md covers Guardrail — where this skill's…, Key facts agents get wrong…, Routing and Security Considerations
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • GUI application via WorkSpaces Applications / AppStream — including dcv session not ready

What it does

Amazon Workspaces Agent Access is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Connects AI agents to remote Windows desktop applications on Amazon WorkSpaces Applications (AppStream 2.0) through the managed Agent Access MCP server, and guides reliable desktop automation. Covers connecting an agent to the MCP endpoint (SigV4, streaming URL, and Active Directory SAML/Domain Join), BLOCKING vs POLLING connect modes, the computer-use tools (screenshot, click, type, key, scroll), screenshot-budget and action-batching discipline, MCP tool forwarding (forwarded tools), session lifecycle and…

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/automation-best-practices.md`, `references/connection-modes.md` and `references/connection-setup.md`).

It sits in Productivity & Automation, covering MCP servers, Desktop control and Red teaming and adversary simulation. It works with Model Context Protocol and Amazon Web Services. The repository describes itself as: Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS. The licence is Apache-2.0.

When your agent uses it

  • Debugging an agent that drives a remote Windows desktop
  • GUI application via WorkSpaces Applications / AppStream — including dcv session not ready
  • Clientdisconnected
  • 400 signing-region

Example prompts

  • “dcv session not ready”
  • “clientdisconnected”
  • “Use the amazon-workspaces-agent-access skill to connect AI agents to remote Windows desktop applications on Amazon WorkSpaces Applications…”
  • “/amazon-workspaces-agent-access”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit bd49cc8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.aws.amazon.com
    • agentaccess-mcp.us-east-1.api.aws

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Amazon Workspaces Agent Access loads about 2.7k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 254 tokens; SKILL.md has 1,084 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~254
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~10k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from aws/agent-toolkit-for-aws at commit bd49cc8, republished under its Apache-2.0 licence (© aws). 1,084 words, ~2,736 tokens.

Download SKILL.mdSave it as .claude/skills/amazon-workspaces-agent-access/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
amazon-workspaces-agent-access
description
Connects AI agents to remote Windows desktop applications on Amazon WorkSpaces Applications (AppStream 2.0) through the managed Agent Access MCP server, and guides reliable desktop automation. Covers connecting an agent to the MCP endpoint (SigV4, streaming URL, and Active Directory SAML/Domain Join), BLOCKING vs POLLING connect modes, the computer-use tools (screenshot, click, type, key, scroll), screenshot-budget and action-batching discipline, MCP tool forwarding (forwarded___ tools), session lifecycle and expire-on-delete, and troubleshooting connection errors. Use when building or debugging an agent that drives a remote Windows desktop or GUI application via WorkSpaces Applications / AppStream — including "dcv session not ready", "client_disconnected", 400 signing-region, POLLING/connection_status, SAML assertion, or forwarded tool questions. Not for Amazon WorkSpaces Personal/Core virtual desktops or general AppStream fleet administration unrelated to agent access.
version
1

Amazon WorkSpaces Applications — Agent Access

Domain expertise for connecting AI agents to remote Windows desktops on Amazon WorkSpaces Applications (AppStream 2.0) via the managed Agent Access MCP server, and for driving those desktops reliably.

How it works: Agent Access is MCP-only — there is no AWS CLI/SDK command that calls the desktop tools. Agents connect to https://agentaccess-mcp.{region}.api.aws/mcp over Streamable HTTP, SigV4-signed with service name agentaccess-mcp, and call MCP tools (screenshot, left_click, type_text, ...) to drive the desktop. The AWS CLI/SDK is used only for setup — appstream create-streaming-url, fleet/stack configuration. mcp-proxy-for-aws handles the SigV4 signing.

Recommended setup: use mcp-proxy-for-aws (Python) as the transport; it signs each request and manages the DELETE lifecycle. Any MCP client that supports Streamable HTTP + SigV4 works. When running the AWS CLI/SDK setup steps (create-streaming-url, stack/fleet configuration), the AWS MCP server is recommended for sandboxed execution and audit logging.

Guardrail — where this skill's own files live (MCP vs local install)

This skill can be loaded two ways, and they resolve the skill's own bundled files from different places. Determine how the skill was loaded before reading a reference:

  • Loaded through the AWS MCP retrieve_skill tool: The skill is not installed on the local filesystem. You MUST fetch each reference via retrieve_skill with the file parameter (e.g. file="references/connection-setup.md"), and use the returned content. Do NOT file_read these paths locally — they do not exist on disk.
  • Installed locally (e.g. .kiro/skills/amazon-workspaces-agent-access/ or ~/.claude/skills/amazon-workspaces-agent-access/): Read files from the local skill directory using relative paths.

This distinction applies only to the skill's own packaged files. User data and session artifacts are always read from and written to the user's working directory. Never fetch or write customer data through retrieve_skill.

Key facts agents get wrong (load the reference before answering in detail)

These are HTTP headers / metadata on the MCP connection — not tool parameters, and there is no connect_to_desktop tool. Do not invent tools or parameters; the desktop tools are exactly those in tools-reference.md.

  • Connect mode. Selected by the X-Amzn-AgentAccess-Connect-Mode HTTP header (value BLOCKING, the default, or POLLING) — sent on the MCP request alongside the streaming-URL/SAML auth. It is NOT a JSON tool argument.

    • ❌ WRONG (common hallucination): calling a connect_to_desktop tool with a connection_mode: "POLLING" parameter, or a session_id/application_id/user_id argument. None of those exist.

    • ✅ RIGHT: set the X-Amzn-AgentAccess-Connect-Mode: POLLING header. Then tools/list initially returns only the connection_status tool; the agent calls connection_status repeatedly until its returned state is CONNECTED, and only then does tools/list return the full desktop tool set (screenshot, left_click, ...). (details: connection-modes.md)

      python
      # Correct POLLING usage — the mode is an HTTP header on the MCP connection:
      async with aws_iam_streamablehttp_client(
          endpoint="https://agentaccess-mcp.us-east-1.api.aws/mcp",  # use YOUR fleet's region
          aws_service="agentaccess-mcp", aws_region="us-east-1",  # region must match the fleet (else 400)
          headers={
              "X-Amzn-AgentAccess-Streaming-Session-Url": streaming_url,
              "X-Amzn-AgentAccess-Connect-Mode": "POLLING",   # header, not a tool arg
          },
      ) as (read, write, _):
          async with ClientSession(read, write) as session:
              await session.initialize()
              # tools/list now returns ONLY connection_status until the desktop is up:
              while json.loads((await session.call_tool("connection_status", {})).content[0].text)["state"] != "CONNECTED":
                  await asyncio.sleep(2)
              tools = await session.list_tools()   # now the full desktop tool set
  • Streaming session (non-domain-joined) is the X-Amzn-AgentAccess-Streaming-Session-Url header. Domain-joined fleets instead pass the SAML assertion + stack ARN via MCP _meta keys aws.agentaccess/workspacesApplicationsSamlAssertion and aws.agentaccess/workspacesApplicationsStackArn. (details: connection-setup.md)

  • Expire-on-delete is the X-Amzn-AgentAccess-Expire-Streaming-Session-On-Delete header (true/false; default false). Expiry happens on the client's explicit HTTP DELETE — mcp-proxy-for-aws sends it automatically on clean close. (details: session-lifecycle.md)

  • Forwarded tools are namespaced by server: forwarded___<server-name>___<tool-name> (e.g. forwarded___filesystem___read_file) — not forwarded___<tool-name>. (details: tool-forwarding.md)

  • COMPUTER_INPUT requires COMPUTER_VISION to also be ENABLED in the stack's AgentAccessConfig. (details: enabling-agent-access.md)

Routing

User needRead
Enable agent access on a stack (AgentAccessConfig: COMPUTER_INPUT/COMPUTER_VISION/FORWARD_MCP_TOOLS, screen resolution/format, prerequisites) — the admin setup step before any agent can connectenabling-agent-access.md
Connect an agent to the MCP server — endpoint, SigV4, streaming URL (non-domain-joined), or Active Directory SAML/Domain Joinconnection-setup.md
Choose BLOCKING vs POLLING; poll connection_status until the desktop is readyconnection-modes.md
The computer-use tool set (mouse, keyboard, screenshot) and their parameterstools-reference.md
Automate reliably — screenshot budget, action batching, trusting UI actions, coordinate planning, dialog recoveryautomation-best-practices.md
Expose your own MCP servers on the fleet as forwarded___<server>___<tool> tools; prefer forwarded tools for file/web taskstool-forwarding.md
Session lifecycle — cleanup, expire-on-delete, idle timeout, one-agent-per-sessionsession-lifecycle.md
Debug an error (exact string → cause → fix): dcv session not ready, client_disconnected, 400/401/403, Unknown tooltroubleshooting.md
Show full SKILL.md (399 more words)Show less

Security Considerations

  • The agent acts under the caller's AWS identity. Every MCP request is SigV4-signed with service agentaccess-mcp; the desktop session runs with those credentials. Grant only the specific agentaccess-mcp actions the agent calls (e.g. InvokeMcp, GetScreenshot, LeftClick, TypeText) and scope them with the agentaccess-mcp:StackArn condition key — avoid a blanket agentaccess-mcp:* or Resource: *. Prefer IAM roles over long-lived users. (Full action list + example: connection-setup.md → IAM permissions.)
  • Screenshots can capture sensitive data. COMPUTER_VISION captures whatever is on the desktop — treat screenshots as potentially containing PII or secrets. If screenshot storage is enabled, the S3 bucket must enforce encryption at rest and in transit and least-privilege access: grant the AppStream service principal only what it needs and the connecting agent only s3:PutObject (see enabling-agent-access.md).
  • Enable only the capabilities you need. COMPUTER_INPUT, COMPUTER_VISION, and FORWARD_MCP_TOOLS are independent — do not enable input/forwarding on stacks that only need vision.
  • Tool forwarding executes code on the fleet. Forwarded MCP servers run on the instance under the session context. Install only trusted servers system-wide, gate with FORWARD_MCP_TOOLS, and scope the CallForwardedTool IAM action by agentaccess-mcp:StackArn (see tool-forwarding.md).
  • Keep a human in the loop where warranted. UserControlMode: VIEW_STOP lets an observer watch the live session and stop the agent. Treat agent-driven desktop actions as capable of arbitrary UI operations.
  • Audit with CloudTrail. Agent session events are logged; tool calls are CloudTrail data events and require a trail configured to log them. Create a trail with agentaccess-mcp data events enabled, encrypt it with SSE-KMS, and add CloudWatch alarms for anomalous patterns (e.g. high screenshot volume, unexpected TypeText, repeated auth failures). If screenshot storage is enabled, turn on S3 server access logging for the bucket.
  • Protect federation material. For domain-joined (SAML) fleets, safeguard the IdP signing certificate and the IAM SAML provider/role trust policy, and do not log the SAML assertion. Traffic is HTTPS + SigV4 — never disable TLS verification.
  • Treat typed input as potentially sensitive. type_text can enter secrets (passwords, tokens); these may then appear in screenshots, screenshot-storage S3, and CloudTrail data events. Avoid typing long-lived secrets into the desktop where possible, and restrict who can read those sinks.
  • Refer to the current Agent Access documentation and AWS security best practices for the latest guidance.

Note: Regional endpoints, feature availability, and quotas change. When precision matters, confirm against the current Agent Access MCP server documentation. The references focus on the values and gotchas that are easy to get wrong.

© aws, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (references) in skills/specialized-skills/end-user-computing-skills/amazon-workspaces-agent-access of aws/agent-toolkit-for-aws.

  • SKILL.md
  • references/automation-best-practices.md
  • references/connection-modes.md
  • references/connection-setup.md
  • references/enabling-agent-access.md
  • references/session-lifecycle.md
  • references/tool-forwarding.md
  • references/tools-reference.md
  • references/troubleshooting.md

Open the folder on GitHubat commit bd49cc8

Compare with similar skills

Amazon Workspaces Agent Access next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Amazon Workspaces Agent Access compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Amazon Workspaces Agent Access this skillaws/agent-toolkit-for-aws2.8k—~2.7kAutomated safety check: PassApache-2.0
Isolated Linux Agent Workspaceagent-sh/agent-workspace-linux185—~2.1kAutomated safety check: PassMIT
Windows CLIsbroenne/mcp-windows105—~1.8kAutomated safety check: PassMIT
Linux Desktop Controlagent-sh/computer-use-linux661—~2.7kAutomated safety check: PassMIT
Browser MCP Agentantibrow/anti-detect-browser-skills9141 repos~4.2kAutomated safety check: WarnMIT
Altic Studioaltic-dev/altic-mcp172—~3.3kAutomated safety check: PassApache-2.0

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Questions about Amazon Workspaces Agent Access

What does Amazon Workspaces Agent Access do?

Connects AI agents to remote Windows desktop applications on Amazon WorkSpaces Applications (AppStream 2.0) through the managed Agent Access MCP server, and guides reliable desktop automation. Amazon Workspaces Agent Access is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization.0) through the managed Agent Access MCP server, and guides reliable desktop automation.

When should I use Amazon Workspaces Agent Access?

Amazon Workspaces Agent Access fits situations like: debugging an agent that drives a remote Windows desktop; GUI application via WorkSpaces Applications / AppStream — including dcv session not ready; clientdisconnected; 400 signing-region.

How do I install Amazon Workspaces Agent Access in Claude Code?

Run `npx skills add aws/agent-toolkit-for-aws --skill amazon-workspaces-agent-access -a claude-code`. Or copy the skill folder (skills/specialized-skills/end-user-computing-skills/amazon-workspaces-agent-access in aws/agent-toolkit-for-aws) into .claude/skills/amazon-workspaces-agent-access in your project. Claude Code loads it when a task matches its description.

How do I install Amazon Workspaces Agent Access in Codex?

Run `npx skills add aws/agent-toolkit-for-aws --skill amazon-workspaces-agent-access -a codex`. Or copy the skill folder (skills/specialized-skills/end-user-computing-skills/amazon-workspaces-agent-access in aws/agent-toolkit-for-aws) into .agents/skills/amazon-workspaces-agent-access in your project. Codex loads it when a task matches its description.

Can I use Amazon Workspaces Agent Access in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aws/agent-toolkit-for-aws --skill amazon-workspaces-agent-access -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/amazon-workspaces-agent-access, .gemini/skills/amazon-workspaces-agent-access, .github/skills/amazon-workspaces-agent-access and .opencode/skills/amazon-workspaces-agent-access in your project.

What does Amazon Workspaces Agent Access need to run?

SKILL.md names no scripts, command-line tools or credentials: Amazon Workspaces Agent Access is instructions for the agent only. Our summary lists: Python 3.

Does Amazon Workspaces Agent Access access the network?

SKILL.md names 2 domains. As links in the text: docs.aws.amazon.com and agentaccess-mcp.us-east-1.api.aws. This is read from the text; nothing was executed.

Is Amazon Workspaces Agent Access safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Amazon Workspaces Agent Access use?

Amazon Workspaces Agent Access is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Amazon Workspaces Agent Access use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.3k tokens, read only when the agent opens those files.

What are the alternatives to Amazon Workspaces Agent Access?

Skills that share tags, products or a category with Amazon Workspaces Agent Access: Isolated Linux Agent Workspace (agent-sh/agent-workspace-linux, 185 stars), Windows CLI (sbroenne/mcp-windows, 105 stars), Linux Desktop Control (agent-sh/computer-use-linux, 661 stars) and Browser MCP Agent (antibrow/anti-detect-browser-skills, 914 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Amazon Workspaces Agent Access?

aws (a GitHub organization, an official publisher) maintains it in aws/agent-toolkit-for-aws, which has 2,816 GitHub stars. The repository holds 138 skills in this directory. The repository was last updated on October 7, 2026.

Source: aws/agent-toolkit-for-aws on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.