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get_projects

Retrieve all projects from Todoist to view and manage your task organization structure.

Instructions

Get all projects from Todoist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main MCP tool handler for 'get_projects'. It calls the TodoistClient's get_projects method and formats the results into a human-readable string list.
    @mcp.tool()
    async def get_projects() -> str:
        """Get all projects from Todoist."""
        _check_client()
        
        projects = await todoist_client.get_projects()
        
        if not projects:
            return "No projects found."
        
        project_list = []
        for project in projects:
            project_info = f"• [{project.id}] {project.name}"
            if project.is_shared:
                project_info += " (Shared)"
            if project.is_favorite:
                project_info += " ⭐"
            project_list.append(project_info)
        
        return f"Found {len(projects)} projects:\n" + "\n".join(project_list)
  • The @mcp.tool() decorator registers the get_projects function as an MCP tool.
    @mcp.tool()
  • TodoistClient helper method that performs the actual API call to retrieve projects from Todoist and parses them into TodoistProject models.
    async def get_projects(self) -> List[TodoistProject]:
        """Get all projects."""
        data = await self._request("GET", "/projects")
        return [TodoistProject(**project) for project in data]
  • Pydantic schema/model for TodoistProject used in parsing API responses.
    class TodoistProject(BaseModel):
        """Represents a Todoist project."""
        id: str
        name: str
        comment_count: int = 0
        order: int = 0
        color: str = "grey"
        is_shared: bool = False
        is_favorite: bool = False
        is_inbox_project: bool = False
        is_team_inbox: bool = False
        view_style: str = "list"
        url: str = ""
        parent_id: Optional[str] = None
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states it 'gets' projects but doesn't specify whether this is a read-only operation, requires authentication, has rate limits, returns paginated results, or what format the output takes. While 'get' implies a safe read operation, the lack of explicit behavioral details leaves significant gaps for an agent.

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 communicates the core purpose without any wasted words. It's appropriately front-loaded with the essential information ('Get all projects from Todoist') and contains no extraneous details. This is an excellent example of conciseness for a simple retrieval tool.

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?

For a zero-parameter tool with an output schema (which handles return values), the description is minimally adequate. It states what the tool retrieves but lacks behavioral context (authentication, rate limits, etc.) and usage guidance relative to siblings. The presence of an output schema reduces the burden, but the description could still benefit from more operational context.

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

Parameters4/5

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

The tool has zero parameters, and schema description coverage is 100% (though empty). The description doesn't need to explain parameters since none exist. It appropriately focuses on what the tool does rather than parameter details, earning a high score for this dimension given the parameterless design.

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 ('Get') and resource ('all projects from Todoist'), making the purpose immediately understandable. It doesn't specifically differentiate from sibling tools like 'get_project' (singular), but the 'all projects' phrasing provides some implicit distinction. The description avoids tautology by specifying what is being retrieved rather than just restating the tool name.

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?

The description provides no guidance on when to use this tool versus alternatives like 'get_project' (singular) or 'get_tasks'. There's no mention of prerequisites, context, or comparison with sibling tools. The agent must infer usage from the tool name and description alone without explicit direction.

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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