AgentDrive MCP Server

drive_recall

Search across agent-written artifacts to recall persistent facts, preferences, and decisions. Provide a query to retrieve relevant results.

Instructions

Recall persistent facts and preferences your agents have written. In v1 this returns semantic search results across artifacts; v1.5 will narrow to auto-extracted facts (preferences, decisions, key entities).

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": {
      "query": "<query>"
    },
    "name": "drive_recall"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes	Recall query — what fact, preference, or decision are you trying to remember?
`top_k`	No	Max results (default 5, max 20)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 30, 2026

TDQS

A3.8/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool performs semantic search (v1) and future versions will narrow to facts, but it does not mention safety, auth requirements, or whether the tool is read-only. The 'recall' verb implies non-destructiveness, but explicit behavioral traits are absent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (two sentences) and front-loads the core purpose. It efficiently covers v1 and future plans. A slight improvement could be separating version details, but it remains clear and non-verbose.

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 tool with no output schema, the description does not explain the return format or structure of results. It mentions 'semantic search results' but omits specifics about pagination or error scenarios. Given the simplicity (2 params), some additional context about expected outcomes would improve completeness.

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?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the 'query' parameter ('what fact, preference, or decision are you trying to remember?') and stating the default for 'top_k' (5) which is not in the schema. This goes beyond just replicating schema info.

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

Purpose5/5

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

The description clearly explains that the tool recalls persistent facts and preferences written by agents, distinguishing it from siblings like 'drive_read' and 'drive_search' by specifying it returns semantic search results across artifacts (v1) and will narrow to auto-extracted facts. The verb 'recall' and resource 'persistent facts and preferences' are specific.

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 implies the tool should be used when trying to remember facts or preferences written by agents, but it does not explicitly state when to use it versus alternatives like 'drive_read' or 'drive_search'. No exclusions or when-not-to-use guidance are provided, making it minimally adequate.

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