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plane-mcp-server

list_work_logs

Retrieve work logs for a specific work item in a project by providing the project and work item UUIDs.

Instructions

List work logs for a work item.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesUUID of the project
work_item_idYesUUID of the work item
paramsNoOptional query parameters as a dictionary

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'list_work_logs' tool. It accepts project_id, work_item_id, and optional params, gets the Plane client context, and calls client.work_items.work_logs.list() to fetch work logs.
    def list_work_logs(
        project_id: str,
        work_item_id: str,
        params: dict[str, Any] | None = None,
    ) -> list[WorkItemWorkLog]:
        """
        List work logs for a work item.
    
        Args:
            project_id: UUID of the project
            work_item_id: UUID of the work item
            params: Optional query parameters as a dictionary
    
        Returns:
            List of WorkItemWorkLog objects
        """
        client, workspace_slug = get_plane_client_context()
        return client.work_items.work_logs.list(
            workspace_slug=workspace_slug,
            project_id=project_id,
            work_item_id=work_item_id,
            params=params,
        )
  • Input schema: project_id (str), work_item_id (str), params (dict[str, Any] | None). Output type: list[WorkItemWorkLog].
    def list_work_logs(
        project_id: str,
        work_item_id: str,
        params: dict[str, Any] | None = None,
    ) -> list[WorkItemWorkLog]:
  • Registration: The function list_work_logs is registered as an MCP tool via the @mcp.tool() decorator in register_work_log_tools().
    def register_work_log_tools(mcp: FastMCP) -> None:
        """Register all work log-related tools with the MCP server."""
    
        @mcp.tool()
        def list_work_logs(
            project_id: str,
            work_item_id: str,
            params: dict[str, Any] | None = None,
        ) -> list[WorkItemWorkLog]:
            """
            List work logs for a work item.
    
            Args:
                project_id: UUID of the project
                work_item_id: UUID of the work item
                params: Optional query parameters as a dictionary
    
            Returns:
                List of WorkItemWorkLog objects
            """
            client, workspace_slug = get_plane_client_context()
            return client.work_items.work_logs.list(
                workspace_slug=workspace_slug,
                project_id=project_id,
                work_item_id=work_item_id,
                params=params,
            )
  • Import of register_work_log_tools in the tools package __init__.py, and it's called at line 35 to register all work log tools.
    from plane_mcp.tools.work_logs import register_work_log_tools
    from plane_mcp.tools.workspaces import register_workspace_tools
    
    
    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)
  • The get_plane_client_context() helper function that initializes and returns a PlaneClient instance with workspace slug, used by list_work_logs to get the client.
    def get_plane_client_context() -> PlaneClientContext:
        """
        Initialize and return a PlaneClient instance with workspace context.
    
        Authentication is handled by the PlaneOAuthProvider, which supports:
        1. Environment variables (PLANE_API_KEY + PLANE_WORKSPACE_SLUG)
        2. HTTP headers (x-api-key + x-workspace-slug)
        3. OAuth access token
    
        Environment variables:
        - PLANE_INTERNAL_BASE_URL: Internal URL for Plane API (preferred for server-to-server calls)
        - PLANE_BASE_URL: Base URL for Plane API (fallback, default: https://api.plane.so)
    
        Returns:
            PlaneClientContext containing configured PlaneClient instance and workspace slug
    
        Raises:
            ConfigurationError: If access token is not available or workspace slug is missing
        """
        base_url = os.getenv("PLANE_INTERNAL_BASE_URL") or os.getenv("PLANE_BASE_URL", "https://api.plane.so")
        workspace_slug = os.getenv("PLANE_WORKSPACE_SLUG", "")
    
        api_key = os.getenv("PLANE_API_KEY", "")
        access_token = None
    
        # Get access token from the OAuth provider (which handles all auth methods)
        stored_access_token: AccessToken | None = get_access_token()
        if stored_access_token:
            # Determine authentication method to use appropriate PlaneClient constructor
            auth_method = stored_access_token.claims.get("auth_method", "oauth")
            token = stored_access_token.token
            workspace_slug = stored_access_token.claims.get("workspace_slug", "")
    
            # For API key auth methods, use api_key parameter; for OAuth, use access_token
            if auth_method in ("api_key_env", "api_key_header"):
                api_key = token
            else:
                access_token = token
    
        if access_token:
            client = PlaneClient(
                base_url=base_url,
                access_token=access_token,
            )
        else:
            client = PlaneClient(
                base_url=base_url,
                api_key=api_key,
            )
    
        return PlaneClientContext(
            client=client,
            workspace_slug=workspace_slug,
        )
Behavior2/5

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

The description lacks any behavioral details such as read-only nature, pagination, ordering, or filtering capabilities. With no annotations, the agent must infer safety and behavior from the name alone.

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

Conciseness3/5

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

The description is concise but overly brief. It captures the core function but lacks structure or detail. A single sentence is acceptable, but more context would improve usability.

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 presence of an output schema, the description does not need to describe return values. However, it omits key contextual details like pagination, sorting, and parameter usage beyond the schema.

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

Parameters2/5

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

The input schema already describes all parameters (100% coverage), so the description adds no new meaning. It only restates the relationship between work logs and work items.

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 verb 'list' and the resource 'work logs for a work item', but it could be more specific about the required context (project and work item IDs). It differentiates from sibling list tools by specifying work logs.

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 versus alternatives like 'get_project_worklog_summary' or other list tools. The description does not mention prerequisites or scope.

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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