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plane-mcp-server

update_cycle

Update an existing cycle's details including name, dates, owner, or external references using project and cycle identifiers.

Instructions

Update a cycle by ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesUUID of the project
cycle_idYesUUID of the cycle
nameNoCycle name
descriptionNoCycle description
start_dateNoCycle start date (ISO 8601 format)
end_dateNoCycle end date (ISO 8601 format)
owned_byNoUUID of the user who owns the cycle
external_sourceNoExternal system source name
external_idNoExternal system identifier
timezoneNoCycle timezone

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
total_issuesNo
cancelled_issuesNo
completed_issuesNo
started_issuesNo
unstarted_issuesNo
backlog_issuesNo
total_estimatesNo
completed_estimatesNo
started_estimatesNo
created_atNo
updated_atNo
deleted_atNo
nameYes
descriptionNo
start_dateNo
end_dateNo
view_propsNo
sort_orderNo
external_sourceNo
external_idNo
progress_snapshotNo
archived_atNo
logo_propsNo
timezoneNo
versionNo
created_byNo
updated_byNo
projectNo
workspaceNo
owned_byNo

Implementation Reference

  • The update_cycle tool handler function. It is decorated with @mcp.tool(), accepts project_id, cycle_id, and optional fields (name, description, start_date, end_date, owned_by, external_source, external_id, timezone). Constructs an UpdateCycle model instance and calls client.cycles.update().
    @mcp.tool()
    def update_cycle(
        project_id: str,
        cycle_id: str,
        name: str | None = None,
        description: str | None = None,
        start_date: str | None = None,
        end_date: str | None = None,
        owned_by: str | None = None,
        external_source: str | None = None,
        external_id: str | None = None,
        timezone: str | None = None,
    ) -> Cycle:
        """
        Update a cycle by ID.
    
        Args:
            workspace_slug: The workspace slug identifier
            project_id: UUID of the project
            cycle_id: UUID of the cycle
            name: Cycle name
            description: Cycle description
            start_date: Cycle start date (ISO 8601 format)
            end_date: Cycle end date (ISO 8601 format)
            owned_by: UUID of the user who owns the cycle
            external_source: External system source name
            external_id: External system identifier
            timezone: Cycle timezone
    
        Returns:
            Updated Cycle object
        """
        client, workspace_slug = get_plane_client_context()
    
        data = UpdateCycle(
            name=name,
            description=description,
            start_date=start_date,
            end_date=end_date,
            owned_by=owned_by,
            external_source=external_source,
            external_id=external_id,
            timezone=timezone,
        )
    
        return client.cycles.update(workspace_slug=workspace_slug, project_id=project_id, cycle_id=cycle_id, data=data)
  • Import of the UpdateCycle model from plane.models.cycles, which serves as the input validation/schema for the update_cycle tool.
        UpdateCycle,
    )
  • The register_cycle_tools function is called by the main tool registration in tools/__init__.py, which registers the update_cycle tool via the @mcp.tool() decorator.
    def register_cycle_tools(mcp: FastMCP) -> None:
        """Register all cycle-related tools with the MCP server."""
    
        @mcp.tool()
        def list_cycles(
            project_id: str,
            params: dict[str, Any] | None = None,
        ) -> list[Cycle]:
            """
            List all cycles in a project.
    
            Args:
                workspace_slug: The workspace slug identifier
                project_id: UUID of the project
                params: Optional query parameters as a dictionary
    
            Returns:
  • The register_tools function calls register_cycle_tools(mcp), which is the registration entry point for the update_cycle tool.
    def register_tools(mcp: FastMCP) -> None:
        """Register all tools with the MCP server."""
        register_project_tools(mcp)
        register_work_item_tools(mcp)
        register_work_item_activity_tools(mcp)
        register_work_item_comment_tools(mcp)
        register_work_item_link_tools(mcp)
        register_work_item_relation_tools(mcp)
        register_work_log_tools(mcp)
        register_cycle_tools(mcp)
        register_user_tools(mcp)
        register_module_tools(mcp)
        register_initiative_tools(mcp)
        register_intake_tools(mcp)
        register_label_tools(mcp)
        register_page_tools(mcp)
        register_work_item_property_tools(mcp)
        register_work_item_type_tools(mcp)
        register_state_tools(mcp)
        register_workspace_tools(mcp)
        register_epic_tools(mcp)
        register_milestone_tools(mcp)
Behavior2/5

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

No annotations exist, so the description must carry the full burden. It only states 'update', implying mutation, but does not disclose if updates are idempotent, partial, or have side effects. The description adds no insight beyond the action.

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

Conciseness4/5

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

The description is a single, concise sentence that is front-loaded. While very brief, it avoids unnecessary detail and is immediately clear, though it could benefit from a bit more context.

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?

Given the tool has 10 optional parameters, an output schema, and no annotations, the description is too sparse. It does not explain the nature of updates (full vs partial), what the output contains, or any special behaviors, leaving the agent under-informed.

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%, so the baseline is 3. The description adds no additional meaning to the parameters beyond what the schema already provides.

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

Purpose4/5

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

The description clearly states the action 'update' and the resource 'cycle', differentiating it from creation, deletion, retrieval, and listing tools. However, it lacks details on which fields can be updated, although the input schema compensates.

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 is provided on when to use this tool, prerequisites, or alternatives. Siblings like create_cycle, archive_cycle, and retrieve_cycle are not mentioned, leaving the agent to infer usage from the name alone.

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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