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Hebbrix

Hebbrix MCP Server

Official
by Hebbrix

hebbrix_remember_many

Store multiple distinct facts from one message in a single batch call, reducing round-trips and rate-limit hits while preserving each fact as separate memory.

Instructions

Store MANY facts in one call. When you've extracted several distinct facts from one user message, use this instead of calling hebbrix_remember N times — it's one round-trip and one rate-limit hit, not N.

Pass a list of short, self-contained facts (one fact per string). Returns {"created", "failed", "memory_ids", ...}. wait_for_index defaults to False here (bulk writes are usually fire-and-forget); set True to block until all are searchable.

Tier note: the single-round-trip batch endpoint requires Starter+; on the free / agent tier this transparently falls back to sequential writes (the result carries "fallback": "sequential"), so it still works but isn't one round-trip on that tier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
factsYes
collection_idNo
wait_for_indexNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.3.20

TDQS

A4.9/5.0
Behavior5/5

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

Annotations are minimal (non-read-only, not idempotent), so the description carries the burden. It discloses return fields, the wait_for_index default and blocking behavior, the tier-based fallback to sequential writes, and the 'fallback': 'sequential' result field. This adds substantial context beyond annotations.

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 compact and front-loaded with the most important point. Each paragraph adds distinct value: usage guidance, parameter behavior, and tier-specific fallback. No fluff or redundant restatement of the schema.

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?

Given the tool's moderate complexity, the presence of an output schema, and sibling-tool context, the description provides sufficient operational context: when to use it, what it returns, how wait_for_index works, and the tier caveat. Only minor param detail (collection_id) is left to the schema, which is acceptable here.

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 description coverage is 0%, so the description must compensate. It clearly explains the facts array format and wait_for_index behavior, but collection_id is not mentioned in the description. Since 2 of 3 parameters receive meaningful semantic elaboration, this is strong but not complete.

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's first sentence, 'Store MANY facts in one call,' uses a specific verb and resource while immediately distinguishing this batch tool from the single-fact sibling hebbrix_remember. It clearly states the batching purpose and avoids ambiguity.

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

Usage Guidelines5/5

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

Explicit guidance is provided: use this tool when extracting several distinct facts from one user message instead of calling hebbrix_remember N times. It also explains the trade-off, including one round-trip and one rate-limit hit, and notes the tier-dependent fallback behavior.

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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