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Glama

Brreg No

by io.github.pipeworx-io

Remember

remember
Idempotent

Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations convey readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds useful behavioral context beyond annotations: 'Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours.' This explains persistence and scoping without contradicting the 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 three sentences, front-loaded with the primary purpose, and every sentence adds value: purpose, usage guidance, storage/persistence details, and sibling tool pairing. No unnecessary words or repetition.

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

Completeness4/5

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

This is a simple tool with 2 parameters and no output schema. The description covers purpose, when to use, persistence details, and relationship with recall/forget. It does not mention return values, but for a save operation this is not a significant gap given the tool's simplicity.

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 description coverage is 100% for both parameters (key and value), each with examples. The description's mention of 'key-value pair' reinforces the schema but adds no new parameter-level details 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.

Purpose5/5

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

The description clearly states the tool's purpose: 'Save data the agent will need to reuse later — across this conversation or across sessions.' It uses a specific verb (save) and resource (data to reuse), and distinguishes itself from sibling tools by saying 'Pair with recall to retrieve later, forget to delete.'

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 gives explicit when-to-use context: 'Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject).' It also mentions alternatives (recall and forget) but does not explicitly state when not to use this tool, so it lacks full exclusion criteria.

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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TDQS

A3.5/5.0
Disambiguation1/5

ask_pipeworx_beta is explicitly identical to ask_pipeworx, and multiple other tools overlap heavily: ai_visibility_check/scan_competitor_ai_presence, discover_tools/suggest_questions, and polymarket_arbitrage/polymarket_edges/polymarket_edge_tracker all sit in nearly the same functional space. An agent would struggle to reliably select the right tool among these clusters.

Naming Consistency3/5

Tool names are consistently snake_case and mostly readable, but the pattern is mixed: get_/search_ verbs coexist with product-prefixed names (pipeworx_*, polymarket_*), noun-style names (entity_profile, recent_changes), and bare verbs (remember, forget). The conventions are not chaotic, but they are not predictable enough for a coherent set.

Tool Count2/5

37 tools is far too many for a server named 'Brreg No,' which should be a focused Norwegian business-registry lookup server. Only a handful of tools actually target Brreg (search_entities, get_entity, get_accounts, get_roles, get_sub_entity, search_sub_entities); the rest are unrelated Pipeworx/Polymarket/meta tools that drown out the core purpose.

Completeness3/5

The core Brreg read surface is present: entity search/lookup, sub-entities, financial accounts, and roles. However, there is no Brreg change/update feed or document-level coverage, and the unrelated generic research tools do not fill that gap. For a registry-focused server, the coverage is workable but not complete.

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