AgentDrive MCP Server

drive_feedback

Retrieve human comments on a file to review feedback from collaborators.

Instructions

Read human comments on a file. Use this to check if humans have left feedback.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workspace_id": "<workspace_id>",
      "file_id": "<file_id>"
    },
    "name": "drive_feedback"
  }
}

Input Schema

Name	Required	Description	Default
`file_id`	Yes	File ID to read comments from
`workspace_id`	Yes	Workspace ID

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 30, 2026

TDQS

B3.3/5.0

Behavior2/5

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

No annotations are provided, so the description carries full burden. It only states the basic function without disclosing behavioral traits like read-only nature, pagination, response format, permission requirements, or behavior when no comments exist. This is insufficient for a tool with no annotation support.

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 consists of two short sentences with zero fluff. Every word adds value, making it highly efficient.

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 simplicity (2 params, no output schema), the description covers the core functionality but omits details about return values, error cases, or how comments are structured. It is adequate for an experienced user but incomplete for an AI agent without context from other drive tools.

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 coverage is 100% with clear descriptions for both parameters (file_id, workspace_id). The description adds no further parameter-level context beyond what the schema already provides. Baseline 3 is appropriate.

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 specifies a clear action ('Read human comments on a file') with a specific resource (comments). It distinguishes from siblings like drive_read (file content) and drive_comment (likely writing comments). However, it could more explicitly differentiate from all siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a usage hint ('Use this to check if humans have left feedback'), which provides context. However, it offers no guidance on when not to use this tool or which sibling alternatives might be better suited for related tasks (e.g., drive_read for file content).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.