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Turbo Quant Memory MCP Server

Turbo Quant Memory MCP Server

by Lexus2016
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_projects

List saved projects with labels and explicitly bound folders to quickly identify and select the right workspace context.

Instructions

List saved projects with labels and explicitly bound folders.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_projects"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose the shape of what comes back (labels and bound folders per project). However, it says nothing about safety, permissions, whether the listing is exhaustive or filtered, or whether a project must be selected first — gaps that matter for a zero-annotation tool.

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?

A single front-loaded sentence naming the verb, the resource, and the included fields, with no filler or hedging. Nothing is wasted and nothing needs reordering.

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?

An output schema exists, so return values need not be explained, and there are no parameters to document. What is missing is context an agent needs before calling: whether the result covers all saved projects or only those visible in the current workspace, and how it relates to select_project.

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 takes zero parameters, so there is no parameter meaning for the description to supply. Baseline 4 applies; the sentence adds only a hint about the content of returned entries, which is beyond schema scope anyway.

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 gives a specific verb ("List") and resource ("saved projects") and adds what each entry carries: labels and explicitly bound folders. That is enough to distinguish it from mutation siblings like bind_project or select_project, though it never names a sibling or clarifies how it relates to list_scopes.

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?

There is no when-to-use guidance at all — no statement of when to call this versus select_project (the action version) or list_scopes. The agent must infer that this is the read-only enumeration counterpart purely from the word "List".

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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