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Hebbrix MCP Server

Hebbrix MCP Server

Official
by Hebbrix
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

hebbrix_extraction_status

Read-onlyIdempotent

Check the status of a smart-ingestion extraction job. Poll until completion to retrieve created or updated atomic memories, or receive an actionable error if the job fails.

Instructions

Poll a smart-ingestion job returned by hebbrix_remember(extract=True).

Returns queued/processing/indexing_pending until terminal, then returns the created/updated atomic memories on completed or an actionable error on failed. Jobs expire after the backend retention window, so poll promptly.

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": {
      "job_id": "<job_id>"
    },
    "name": "hebbrix_extraction_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYes
collection_idNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.1

TDQS

A4.4/5.0
Behavior5/5

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

The description reveals behavior beyond the safe annotations: it describes the status lifecycle (queued/processing/indexing_until terminal), what happens at completion vs failure, and a retention-window expiration. This gives the agent crucial information about repeated polling and timeout risks that would otherwise be invisible.

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?

Three crisp sentences, not a single redundant word. The main purpose is front-loaded, then state-transition and expiration hazards are explained in two more lines. Ideal for parsing by an agent and compared to verbose descriptions.

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?

For a simple polling tool with an output schema available, the description fully covers the workflow context: how the job is created, what states it transitions through, the terminal results, and the warning about expiry. No critical context appears to be missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry parameter semantics. It only implies that job_id is the job returned by hebbrix_remember, but it never mentions collection_id, its purpose, or usage. Two parameters, one optional, are left mostly undocumented semantically.

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 opens with a specific action, 'Poll a smart-ingestion job returned by hebbrix_remember(extract=True)', which clearly defines the resource and provenance. This makes the tool obvious distinct from all sibling memory-management tools, which focus on reading, writing, searching, or deleting rather than polling a job.

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?

It tells users exactly when to invoke this tool: after hebbrix_remember(extract=True). It also gives an imperative 'poll promptly' because jobs expire. It doesn't list alternatives or explicit when-not scenarios, but this is naturally the only polling tool in the set, so the context is clear enough.

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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