This record as markdown: /tools/inggerman-mcps/tf-workspace-select.md
What tf_workspace_select does on MCP Framework Personal
AI agents use tf_workspace_select to create or update resources in MCP Framework Personal, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your MCP Framework Personal environment.
Why tf_workspace_select is rated Medium
An AI agent can call tf_workspace_select faster than any human can review: one bad instruction and it creates or modifies resources in MCP Framework Personal by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs tf_workspace_select safely
PolicyLayer is an MCP gateway: it sits between your AI agents and MCP Framework Personal, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For tf_workspace_select, this is the rule to start with:
tf_workspace_select stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect MCP Framework Personal, apply this rule, and every tf_workspace_select call is checked against it from then on.
Questions about tf_workspace_select
Selecciona un workspace. It is categorised as a Write tool in the MCP Framework Personal MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the MCP Framework Personal MCP server in PolicyLayer and add a rule for tf_workspace_select: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches MCP Framework Personal. Nothing to install.
tf_workspace_select is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the tf_workspace_select rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for tf_workspace_select. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
tf_workspace_select is provided by the MCP Framework Personal MCP server (inggerman/mcps). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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