mem0-mcp-selfhosted

memory_task_status

Retrieve the status of an asynchronous memory task, showing state, resulting memory IDs, and error details for completed or failed tasks.

Instructions

Status of an asynchronous add_memory task.

    States: pending | processing | done | failed_retryable | dead.
    When done, ``result.memory_ids`` lists the memories created/updated
    (fetch them with get_memory) and ``result.events`` includes any
    SUPERSEDED markings. ``last_error`` explains failed/dead tasks.

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": {
      "task_id": "<task_id>"
    },
    "name": "memory_task_status"
  }
}

Input Schema

Name	Required	Description	Default
`task_id`	Yes	Task id returned by a queued add_memory call (tsk_...).

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.0.0Jul 9, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It transparently lists possible states (pending, processing, done, failed_retryable, dead) and explains result fields including 'result.memory_ids', 'result.events' with SUPERSEDED markings, and 'last_error'. It does not indicate destructive behavior, which is appropriate for a read-only status check.

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, well-structured paragraph with clear front-loading of purpose. Every sentence adds value: states enumeration, result fields, error explanation. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the description provides rich behavioral context (states, result fields, error handling) that fully covers the tool's functionality. It includes details like SUPERSEDED events which add valuable context.

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%, and the description of task_id ('Task id returned by a queued add_memory call (tsk_...).') essentially repeats the schema's description. The description adds no new semantic value beyond the schema, so baseline of 3 is appropriate.

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 states the tool returns the status of an asynchronous add_memory task, with specific verb 'status' and resource 'memory_task'. It distinguishes from siblings like add_memory and memory_queue_status by focusing on a single task's status.

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

Usage Guidelines4/5

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

The description provides guidance on how to interpret results (fetch memories with get_memory, check last_error for failure) and implies use after an add_memory call. However, it does not explicitly contrast with sibling memory_queue_status or give explicit when-not-to-use scenarios.

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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