Amazon Workspaces Agent Access
AWSOfficialPublished by AWS
- Skill
- Tool integration
- Cloud and DevOps
- Apache-2.0
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides domain expertise for integrating AI agents with Amazon WorkSpaces Applications (AppStream 2.0) using the Agent Access MCP server. It covers the technical requirements for establishing secure connections, including SigV4 signing, streaming URL handling, and Active Directory SAML authentication. The skill details how to manage desktop sessions, implement reliable automation through screenshot and action-batching discipline, and utilize MCP tool forwarding. It also provides guidance on troubleshooting common connection errors and configuring stack-level settings for computer input and vision.
What it does
- Guides the setup of Agent Access MCP connections using SigV4 and streaming URLs.
- Explains the difference between BLOCKING and POLLING connection modes.
- Provides best practices for reliable desktop automation, including screenshot budgets and action batching.
- Details the use of computer-use tools like screenshot, click, type, key, and scroll.
- Describes how to expose and use forwarded MCP tools within the remote desktop session.
- Offers troubleshooting steps for common connection and session lifecycle errors.
When to use it
- When building an AI agent that needs to interact with Windows GUI applications on AppStream 2.0.
- When debugging connection issues such as dcv session not ready or client_disconnected errors.
- When optimizing agent performance to reduce token usage and latency in desktop automation.
- When configuring stack-level security and permissions for agent-driven desktop access.
Advantages
- Enables secure, agent-driven automation of remote Windows environments.
- Provides clear patterns for managing session lifecycles and connection states.
- Reduces token consumption through recommended batching and screenshot strategies.
- Supports integration with existing MCP servers via tool forwarding.
Usage examples
- “How do I configure my agent to wait for the desktop to be ready before sending commands?”
- The agent is instructed to use the POLLING connection mode by setting the X-Amzn-AgentAccess-Connect-Mode header to POLLING and repeatedly calling the connection_status tool until the state is CONNECTED.
- “My agent is burning too many tokens on screenshots. How can I optimize this?”
- The agent is guided to implement a screenshot budget, taking only one screenshot to establish state, performing 3-5 actions, and verifying outcomes by artifact rather than intermediate steps.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/aws/amazon-workspaces-agent-access/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip amazon-workspaces-agent-access.zip -d .agents/skills
Documentation by AWS
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_skilltool: The skill is not installed on the local filesystem. You MUST fetch each reference viaretrieve_skillwith thefileparameter (e.g.file="references/connection-setup.md"), and use the returned content. Do NOTfile_readthese 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-ModeHTTP header (valueBLOCKING, the default, orPOLLING) — 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_desktoptool with aconnection_mode: "POLLING"parameter, or asession_id/application_id/user_idargument. None of those exist.✅ RIGHT: set the
X-Amzn-AgentAccess-Connect-Mode: POLLINGheader. Thentools/listinitially returns only theconnection_statustool; the agent callsconnection_statusrepeatedly until its returned state isCONNECTED, and only then doestools/listreturn the full desktop tool set (screenshot,left_click, ...). (details: connection-modes.md)# 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-Urlheader. Domain-joined fleets instead pass the SAML assertion + stack ARN via MCP_metakeysaws.agentaccess/workspacesApplicationsSamlAssertionandaws.agentaccess/workspacesApplicationsStackArn. (details: connection-setup.md)Expire-on-delete is the
X-Amzn-AgentAccess-Expire-Streaming-Session-On-Deleteheader (true/false; defaultfalse). Expiry happens on the client's explicit HTTPDELETE—mcp-proxy-for-awssends 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) — notforwarded___<tool-name>. (details: tool-forwarding.md)COMPUTER_INPUTrequiresCOMPUTER_VISIONto also be ENABLED in the stack'sAgentAccessConfig. (details: enabling-agent-access.md)
Routing
| User need | Read |
|---|---|
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 connect | enabling-agent-access.md |
| Connect an agent to the MCP server — endpoint, SigV4, streaming URL (non-domain-joined), or Active Directory SAML/Domain Join | connection-setup.md |
Choose BLOCKING vs POLLING; poll connection_status until the desktop is ready | connection-modes.md |
| The computer-use tool set (mouse, keyboard, screenshot) and their parameters | tools-reference.md |
| Automate reliably — screenshot budget, action batching, trusting UI actions, coordinate planning, dialog recovery | automation-best-practices.md |
Expose your own MCP servers on the fleet as forwarded___<server>___<tool> tools; prefer forwarded tools for file/web tasks | tool-forwarding.md |
| Session lifecycle — cleanup, expire-on-delete, idle timeout, one-agent-per-session | session-lifecycle.md |
Debug an error (exact string → cause → fix): dcv session not ready, client_disconnected, 400/401/403, Unknown tool | troubleshooting.md |
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 specificagentaccess-mcpactions the agent calls (e.g.InvokeMcp,GetScreenshot,LeftClick,TypeText) and scope them with theagentaccess-mcp:StackArncondition key — avoid a blanketagentaccess-mcp:*orResource: *. Prefer IAM roles over long-lived users. (Full action list + example: connection-setup.md → IAM permissions.)Screenshots can capture sensitive data.
COMPUTER_VISIONcaptures 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 onlys3:PutObject(see enabling-agent-access.md).Enable only the capabilities you need.
COMPUTER_INPUT,COMPUTER_VISION, andFORWARD_MCP_TOOLSare 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 theCallForwardedToolIAM action byagentaccess-mcp:StackArn(see tool-forwarding.md).Keep a human in the loop where warranted.
UserControlMode: VIEW_STOPlets 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-mcpdata events enabled, encrypt it with SSE-KMS, and add CloudWatch alarms for anomalous patterns (e.g. high screenshot volume, unexpectedTypeText, 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_textcan 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.
Files
- ATTRIBUTION.mdAdded by AutoGineer958 B
- LICENSELicence file added by AutoGineer9.9 KiB
- NOTICELicence file added by AutoGineer67 B
- SKILL.md10.7 KiB
- references/automation-best-practices.md3.4 KiB
- references/connection-modes.md2.1 KiB
- references/connection-setup.md7.3 KiB
- references/enabling-agent-access.md3.9 KiB
- references/session-lifecycle.md3.0 KiB
- references/tool-forwarding.md3.4 KiB
- references/tools-reference.md2.3 KiB
- references/troubleshooting.md3.1 KiB
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 MCP server, Needs Python
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
- AWS
- Publisher
- AWS (Official)
- Source
- aws/agent-toolkit-for-aws · skills/specialized-skills/end-user-computing-skills/amazon-workspaces-agent-access · commit 0a218f8
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- NOTICE (added by AutoGineer from NOTICE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by AWS.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download amazon-workspaces-agent-access.zip