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plane-mcp-server

retrieve_work_item_activity

Retrieve a specific activity from a work item using project, work item, and activity IDs.

Instructions

Retrieve a specific activity for a work item.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesUUID of the project
work_item_idYesUUID of the work item
activity_idYesUUID of the activity

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
created_atNo
updated_atNo
deleted_atNo
verbNo
fieldNo
old_valueNo
new_valueNo
commentNo
attachmentsNo
old_identifierNo
new_identifierNo
epochNo
projectYes
workspaceYes
issueNo
issue_commentNo
actorNo

Implementation Reference

  • The main handler function for the 'retrieve_work_item_activity' tool. It accepts project_id, work_item_id, and activity_id, then calls the Plane client's work_items.activities.retrieve() method with workspace context.
    def retrieve_work_item_activity(
        project_id: str,
        work_item_id: str,
        activity_id: str,
    ) -> WorkItemActivity:
        """
        Retrieve a specific activity for a work item.
    
        Args:
            project_id: UUID of the project
            work_item_id: UUID of the work item
            activity_id: UUID of the activity
    
        Returns:
            WorkItemActivity object
        """
        client, workspace_slug = get_plane_client_context()
        return client.work_items.activities.retrieve(
            workspace_slug=workspace_slug,
            project_id=project_id,
            work_item_id=work_item_id,
            activity_id=activity_id,
        )
  • The registration function that uses @mcp.tool() decorator to register retrieve_work_item_activity as an MCP tool.
    def register_work_item_activity_tools(mcp: FastMCP) -> None:
        """Register all work item activity-related tools with the MCP server."""
  • The function signature defines the input schema: project_id (str), work_item_id (str), activity_id (str). Return type is WorkItemActivity from plane.models.
    def retrieve_work_item_activity(
        project_id: str,
        work_item_id: str,
        activity_id: str,
    ) -> WorkItemActivity:
  • Top-level registration: register_work_item_activity_tools(mcp) is called in the register_tools function to include all work item activity 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)
  • Helper function get_plane_client_context() used by the handler to obtain the authenticated PlaneClient instance and workspace slug.
    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?

With no annotations, the description carries full burden. It only states 'Retrieve' implying read-only, but no details on error handling, authorization needs, or side effects. The lack of annotations and minimal description leaves behavioral gaps.

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 sentence with no wasted words. It is concise and front-loaded, fulfilling its purpose efficiently.

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

Completeness3/5

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 and full parameter coverage, the description is minimally complete. However, it lacks usage context and behavioral notes, making it just adequate for a simple retrieve operation.

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 description coverage is 100%, so the schema provides parameter details. The description adds no additional meaning beyond the schema, resulting in a baseline score of 3.

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 'Retrieve' and the resource 'specific activity for a work item'. It distinguishes from the sibling 'list_work_item_activities' which retrieves multiple, but could be more explicit about fetching by ID.

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 the sibling 'list_work_item_activities'. The description does not mention when to prefer this tool or any prerequisites.

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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