# Give your agents a place to do lasting work. Reviewed: 2026-10-18 Canonical: https://clankercloud.ai/learn/ai-agent-workspace An AI agent workspace keeps the inputs, instructions, tools, and saved results for work that continues across tasks. Clanker Workspace provides Projects, Sessions, configurable Agents, file review, and selected execution options. Use its browser Agents or connect a compatible external assistant, then preserve checked results in the Project. ## What you are working toward A Project that an agent can use today and another authorized task can understand later. ## Start with - One body of work with a clear owner - Approved source files and a required saved output - A browser Agent or a compatible authorized external client ## What makes a workspace useful to an agent? An agent needs more than a prompt when a job spans several conversations. It needs to know which evidence is current, what the user authorized, where to save its work, and what remains unfinished. A useful workspace makes those answers recoverable from files and task records that a person can inspect. In Clanker, a Project groups related files and instructions. A Session records a particular conversation and its work. An Agent supplies a role, method, and selected capabilities. These parts let you preserve an engagement or research effort while changing the assistant or the next task. They do not remove the need to check an answer. ## Choose Clanker for a complete work cycle Consider Clanker when the job should produce a durable decision brief, source table, document, spreadsheet, or App, and someone needs to return to that work. For example, an agent can compare an approved requirements file with supplier proposals, save the evidence and decision, then leave an unresolved-questions note for a later review. The concrete benefit is the assembled workflow: persistent Project material, a reusable Agent, selected Tools, a Session record, and visible saved outputs. Evaluate that combination on your own task. A chat answer, a generated file, and an accepted business decision are separate milestones; identify which one your workflow actually needs. ## Keep a compatible assistant and connect its tools Claude, ChatGPT, OpenClaw, Hermes, and other compatible clients can reach hosted Workspace through the supported MCP connection. Client version, account access, organization policy, and approved permissions determine whether the route works. First ask the client to find the intended Project and read one known file. The external assistant keeps its own reasoning and provider usage. Workspace supplies the tools exposed to that connection. MCP and the separately authenticated HTTP API have different coverage; neither implies every native Workspace tool is available. Selecting a Project identifies task context, while the OAuth grant can cover the connected user’s accessible Workspace. Sources: - [Clanker: external-agent access, permissions, and managed Sessions](https://clankercloud.ai/workspace-agents) ## Separate lasting work from active compute Saved Project context is different from a running machine. Ordinary writing and file tasks can start in a browser Session. A task needing scripts, a website interaction, or a specific local application may need a cloud environment or an explicitly connected computer. Choose the environment after identifying that dependency. A saved BYOA registration is not a permanently running process. Supported cloud agent tasks use bounded compute, and successfully saved state can be restored for later work. Unsaved process state can be lost. A standalone Sandbox API runtime has its own identity, expiry, and storage rules; it is not the same resource as your Workspace Project. ## Use the workspace to build a reusable specialist Once a task produces a result you can check, turn its stable method into a custom Agent. Define the role, accepted inputs, source rules, selected capabilities, exception behavior, and output checks. Keep changing client or project evidence with the Project rather than embedding every temporary fact into the reusable role. This is the practical agent-factory path: specify a job, configure a specialist, test it with normal and incomplete inputs, and inspect its saved work. Build several narrow roles only when each has a distinct responsibility. A researcher, reviewer, and formatter should exchange named artifacts rather than rely on an assumed shared conversation. ## Prove the handoff before expanding the workflow Start with a small approved packet and one deliverable. Open the saved file in Preview or Files, verify consequential statements, then ask for one correction. Finish with a handoff that identifies source versions, current outputs, unresolved questions, and the next permitted step. Read that handoff in a fresh task. Add recurring execution only after the task and input refresh process work. Native Loops and Schedules have their own settings; connecting an assistant does not create one. Review actual usage, stop unneeded environments, and confirm the exact data arrangement for sensitive work. A persistent workspace is useful when the next task can resume from checked evidence. ## Try this prompt Copy into a Workspace Session. Opening Workspace does not send it automatically. ```text Help me set up a Clanker Workspace Project for a repeatable agent task. First identify the decision, approved inputs, required saved output, and review owner. Recommend only the environment and tools this task needs. Use the current connection guide if I choose an external assistant. Complete one bounded example, read back its saved output, and leave handoff.md with source versions, confirmed results, unresolved questions, and the next permitted action. Do not assume any private conversation is synchronized or start recurring work. ``` ## Before using the result - The Project contains the actual approved sources and checked output. - The active client can use the tools required for this task. - A later task can resume from the saved handoff. - Compute lifetime, access, and usage are understood separately. ## Common questions ### What is an AI agent workspace? It is a working setup where agents can access approved context and tools, record a task, and leave inspectable results for later use. In Clanker, Projects, Sessions, configurable Agents, saved files, and selected execution options form that setup. ### Can Clanker be a workspace for Claude and ChatGPT? Yes, through a compatible client and the supported authorized MCP connection. Availability and exposed tools depend on the client, account policies, and granted permissions. The connection does not automatically synchronize private Claude or ChatGPT conversations. ### Can a workspace also be an agent factory? Clanker lets you configure and test reusable Agents alongside Project sources and saved results. Use a specification and acceptance cases to build a repeatable role; creating the role alone does not establish reliable unattended execution. ## Sources - [Clanker: Workspace product behavior and feature availability](https://clankercloud.ai/faq) - [Clanker: external-agent access, permissions, and managed Sessions](https://clankercloud.ai/workspace-agents) - [Clanker: current agent instructions and HTTP access](https://workspace.clankercloud.ai/for-agents.md) - [Clanker: BYOA setup, runtime, saved state, and usage](https://workspace.clankercloud.ai/#page=faq&tab=articles&article=bring-your-own-agent) - [Clanker: standalone Sandbox API contract](https://clankercloud.ai/api-docs) ## Related - [Choose an environment by what the agent must reach.](https://clankercloud.ai/learn/choose-ai-agent-environment) - [Build an Agent you can test, reuse, and hand over.](https://clankercloud.ai/learn/ai-agent-factory) - [Design context that survives an assistant change.](https://clankercloud.ai/learn/design-agent-project-context) - [A small packet the next agent can verify.](https://clankercloud.ai/templates/agent-handoff-pack) - [Give the Agent a test with an answer you can check.](https://clankercloud.ai/templates/agent-acceptance-test) [Open Workspace](https://workspace.clankercloud.ai) [Current pricing and usage](https://clankercloud.ai/pricing)