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Waldur MCP Server

Official
by waldur
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Python
Remote

list_projects

Retrieve all projects from the Waldur MCP Server to manage and organize cloud resources efficiently.

Instructions

List all projects

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/waldur_mcp_server/server.py:73-76 (handler)
    The handler and registration for the 'list_projects' tool. It is a simple wrapper that calls the Waldur API's projects_list function asynchronously using the authenticated client.
    @mcp.tool()
async def list_projects() -> list[Project]:
    """List all projects"""
    return await projects_list.asyncio(client=client)

Tool Definition Quality

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'List all projects' implies a read operation, but it doesn't specify whether this is paginated, requires authentication, has rate limits, or what the return format is. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 'List all projects' is extremely concise with zero waste—it's a single, front-loaded phrase that directly states the action and resource. Every word earns its place, making it efficient for an agent to parse.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'projects' entails, the return format, or any behavioral traits like pagination or errors. For a tool that likely returns a list of items, more context is needed to guide the agent effectively.

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 0 parameters, and schema description coverage is 100% (since there are no parameters to describe). The description doesn't need to add parameter semantics, so a baseline score of 4 is appropriate as it doesn't introduce confusion or redundancy.

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

Purpose3/5

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

The description 'List all projects' clearly states the verb ('List') and resource ('projects'), making the purpose understandable. However, it lacks specificity about scope or filtering, and doesn't differentiate from sibling tools like 'list_customers' or 'list_resources' beyond the resource 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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention context, prerequisites, or exclusions, and with sibling tools like 'query' that might overlap in functionality, the agent receives no help in tool 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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