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update_workspace_features

Enable or disable workspace features such as project grouping, initiatives, teams, customers, wiki, and program increments.

Instructions

Update features of the current workspace.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_groupingNoEnable/disable project grouping feature
initiativesNoEnable/disable initiatives feature
teamsNoEnable/disable teams feature
customersNoEnable/disable customers feature
wikiNoEnable/disable wiki feature
piNoEnable/disable PI (Program Increment) feature

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_groupingYes
initiativesYes
teamsYes
customersYes
wikiYes
piYes

Implementation Reference

  • The update_workspace_features tool handler function. It accepts optional boolean parameters for each workspace feature (project_grouping, initiatives, teams, customers, wiki, pi), builds a dictionary of only non-None values, constructs a WorkspaceFeature object, and calls client.workspaces.update_features() to persist the changes.
    def update_workspace_features(
        project_grouping: bool | None = None,
        initiatives: bool | None = None,
        teams: bool | None = None,
        customers: bool | None = None,
        wiki: bool | None = None,
        pi: bool | None = None,
    ) -> WorkspaceFeature:
        """
        Update features of the current workspace.
    
        Args:
            project_grouping: Enable/disable project grouping feature
            initiatives: Enable/disable initiatives feature
            teams: Enable/disable teams feature
            customers: Enable/disable customers feature
            wiki: Enable/disable wiki feature
            pi: Enable/disable PI (Program Increment) feature
    
        Returns:
            Updated WorkspaceFeature object
        """
        client, workspace_slug = get_plane_client_context()
    
        # Build data dict with only non-None values
        feature_data: dict[str, bool] = {}
        if project_grouping is not None:
            feature_data["project_grouping"] = project_grouping
        if initiatives is not None:
            feature_data["initiatives"] = initiatives
        if teams is not None:
            feature_data["teams"] = teams
        if customers is not None:
            feature_data["customers"] = customers
        if wiki is not None:
            feature_data["wiki"] = wiki
        if pi is not None:
            feature_data["pi"] = pi
    
        data = WorkspaceFeature(**feature_data)
    
        return client.workspaces.update_features(workspace_slug=workspace_slug, data=data)
  • The @mcp.tool() decorated function that registers update_workspace_features as an MCP tool alongside the tool handler body.
    @mcp.tool()
    def update_workspace_features(
        project_grouping: bool | None = None,
        initiatives: bool | None = None,
        teams: bool | None = None,
        customers: bool | None = None,
        wiki: bool | None = None,
        pi: bool | None = None,
    ) -> WorkspaceFeature:
        """
        Update features of the current workspace.
    
        Args:
            project_grouping: Enable/disable project grouping feature
            initiatives: Enable/disable initiatives feature
            teams: Enable/disable teams feature
            customers: Enable/disable customers feature
            wiki: Enable/disable wiki feature
            pi: Enable/disable PI (Program Increment) feature
    
        Returns:
            Updated WorkspaceFeature object
        """
        client, workspace_slug = get_plane_client_context()
    
        # Build data dict with only non-None values
        feature_data: dict[str, bool] = {}
        if project_grouping is not None:
            feature_data["project_grouping"] = project_grouping
        if initiatives is not None:
            feature_data["initiatives"] = initiatives
        if teams is not None:
            feature_data["teams"] = teams
        if customers is not None:
            feature_data["customers"] = customers
        if wiki is not None:
            feature_data["wiki"] = wiki
        if pi is not None:
            feature_data["pi"] = pi
    
        data = WorkspaceFeature(**feature_data)
    
        return client.workspaces.update_features(workspace_slug=workspace_slug, data=data)
  • The register_workspace_tools function that registers all workspace tools (including update_workspace_features) with the MCP server via @mcp.tool() decorator.
    def register_workspace_tools(mcp: FastMCP) -> None:
        """Register all workspace-related tools with the MCP server."""
    
        @mcp.tool()
        def get_workspace_members() -> list[UserLite]:
            """
            Get all members of the current workspace.
    
            Returns:
                List of UserLite objects representing workspace members
            """
            client, workspace_slug = get_plane_client_context()
            return client.workspaces.get_members(workspace_slug=workspace_slug)
    
        @mcp.tool()
        def get_workspace_features() -> WorkspaceFeature:
            """
            Get features of the current workspace.
    
            Returns:
                WorkspaceFeature object containing feature flags
            """
            client, workspace_slug = get_plane_client_context()
            return client.workspaces.get_features(workspace_slug=workspace_slug)
    
        @mcp.tool()
        def update_workspace_features(
            project_grouping: bool | None = None,
            initiatives: bool | None = None,
            teams: bool | None = None,
            customers: bool | None = None,
            wiki: bool | None = None,
            pi: bool | None = None,
        ) -> WorkspaceFeature:
            """
            Update features of the current workspace.
    
            Args:
                project_grouping: Enable/disable project grouping feature
                initiatives: Enable/disable initiatives feature
                teams: Enable/disable teams feature
                customers: Enable/disable customers feature
                wiki: Enable/disable wiki feature
                pi: Enable/disable PI (Program Increment) feature
    
            Returns:
                Updated WorkspaceFeature object
            """
            client, workspace_slug = get_plane_client_context()
    
            # Build data dict with only non-None values
            feature_data: dict[str, bool] = {}
            if project_grouping is not None:
                feature_data["project_grouping"] = project_grouping
            if initiatives is not None:
                feature_data["initiatives"] = initiatives
            if teams is not None:
                feature_data["teams"] = teams
            if customers is not None:
                feature_data["customers"] = customers
            if wiki is not None:
                feature_data["wiki"] = wiki
            if pi is not None:
                feature_data["pi"] = pi
    
            data = WorkspaceFeature(**feature_data)
    
            return client.workspaces.update_features(workspace_slug=workspace_slug, data=data)
  • Import of register_workspace_tools from the workspaces module, which is called by register_tools() to register all workspace tools including update_workspace_features.
    from plane_mcp.tools.workspaces import register_workspace_tools
  • Call to register_workspace_tools(mcp) which registers the update_workspace_features tool with the MCP server.
    register_workspace_tools(mcp)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavioral traits. It only states the high-level action, missing details on mutability, permissions, or that only provided parameters are updated. The schema implies toggling, but the description does not clarify.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single efficient sentence that immediately states the purpose. No redundant information, perfectly front-loaded for an agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite an output schema, the description is too brief. It fails to explain that only provided parameters are updated (default null) and does not mention the need for appropriate permissions. This gap could lead to incorrect invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for each parameter. The tool description adds nothing beyond the schema, so baseline 3 is appropriate. It does not elaborate on how parameters like 'project_grouping' affect the workspace.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Update features of the current workspace' clearly identifies the action (update) and resource (workspace features). It distinguishes from sibling tools like 'update_project_features' and 'get_workspace_features' by specifying the workspace scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. For example, it does not suggest checking current features via 'get_workspace_features' before updating, nor does it explain the effect of omitting parameters (default null leaves unchanged).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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