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plane-mcp-server

list_modules

Retrieve all modules in a specified project by providing the project ID. Optional parameters allow filtering or pagination for targeted results.

Instructions

List all modules in a project.

Input Schema

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

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The actual handler function for the 'list_modules' tool. Decorated with @mcp.tool() and defined inside register_module_tools. Calls client.modules.list() with workspace_slug, project_id, and optional params, returning results from a PaginatedModuleResponse.
    @mcp.tool()
    def list_modules(
        project_id: str,
        params: dict[str, Any] | None = None,
    ) -> list[Module]:
        """
        List all modules in a project.
    
        Args:
            workspace_slug: The workspace slug identifier
            project_id: UUID of the project
            params: Optional query parameters as a dictionary
    
        Returns:
            List of Module objects
        """
        client, workspace_slug = get_plane_client_context()
        response: PaginatedModuleResponse = client.modules.list(
            workspace_slug=workspace_slug, project_id=project_id, params=params
        )
        return response.results
  • Imports the schema types (Module, PaginatedModuleResponse) used by list_modules for type hints and return types.
    from plane.models.modules import (
        CreateModule,
        Module,
        PaginatedArchivedModuleResponse,
        PaginatedModuleResponse,
        PaginatedModuleWorkItemResponse,
        UpdateModule,
    )
  • The registration function that decorates list_modules with @mcp.tool() to register it with the MCP server.
    def register_module_tools(mcp: FastMCP) -> None:
        """Register all module-related tools with the MCP server."""
  • Called from register_tools() to register all module tools including list_modules.
    register_module_tools(mcp)
  • Imports the helper function get_plane_client_context used by list_modules.
    from plane_mcp.client import get_plane_client_context
Behavior1/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only states the basic function without revealing details like pagination, filtering scope (e.g., active vs archived), or any side effects. This is insufficient.

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 a single short sentence, which is concise. However, it omits critical details needed for effective use, making it under-specified. It is not optimally sized given the 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 existence of an output schema, the description need not detail return values. However, it fails to explain key contextual aspects like whether it lists all modules (including archived?) or only active ones, and it does not differentiate from similar list tools. Incomplete for the tool's complexity.

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?

Since schema description coverage is 100%, the baseline is 3. The description adds no additional meaning beyond the schema's documentation of `project_id` and `params`. It meets the minimum but does not enhance understanding.

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 (list) and resource (modules) within a project. However, it does not explicitly distinguish from sibling tools like `list_archived_modules`, though the naming convention partially compensates. A 4 indicates clear purpose but with room for differentiation.

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 such as `list_archived_modules`, `retrieve_module`, or `list_module_work_items`. The agent must infer from the name alone, providing no explicit context for selection.

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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