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Glama

Udbud Dk

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

A4.5/5.0
Behavior4/5

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

Annotations include idempotentHint, destructiveHint, readOnlyHint. Description adds scoping by identifier, persistence differences for authenticated vs anonymous (24h). No contradictions.

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?

Concise, front-loaded with purpose. Every sentence adds information without 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?

Simple tool with 2 required params and no output schema. Description fully explains usage, storage behavior, and complementary tools. No gaps.

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?

Input schema covers both key and value with descriptions. Description adds context (e.g., key examples like 'subject_property') but does not significantly exceed schema. Baseline 3 justified.

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?

Clear verb+resource: 'Save data the agent will need to reuse later.' Distinguishes from siblings by naming recall and forget, and specifying key-value pair storage.

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?

Explicitly says when to use: 'when you discover something worth carrying forward.' Recommends pairing with recall and forget, providing clear guidance on alternatives.

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

All Udbud Dk toolsInspect
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TDQS

A3.8/5.0
Disambiguation2/5

Several tools form near-overlapping clusters: ask_pipeworx and ask_pipeworx_beta are explicitly identical in behavior, while ask_pipeworx, ask_pipeworx_grounded, and deep_research have overlapping scopes. The five polymarket tools also share a common prediction-market domain and could be confused despite detailed descriptions. Some boundaries between 'meta' tools such as discover_tools, suggest_questions, and ask_pipeworx are also fuzzy.

Naming Consistency3/5

The majority of tools use lowercase snake_case and many follow a verb_noun pattern (ask_pipexors, search_within, generate_llms_txt, destroy_tools), which is readable. However, there are inconsistent orderings like ai_visibility_check and dk_tender_search, plus several one-word verb tools (remember, forget, recall) alongside noun_verb forms. So the style is mostly regular but does not follow a single consistent pattern.

Tool Count2/5

34 tools is very ot heavy for a general-purpose data platform, but the server name 'Udbud Dk' implies a narrow Danish tender scope. Only 3 of the 34 tools actually concern Danish procurement, while the rest form a broad question-answering, prediction-market, subscription, and memory platform. The count feels bloated and mismatched relative to the apparent server focus.

Completeness3/5

For the broad data domain, the server covers a wide range: lookup, grounded answers, entity resolution, fact-checking, company profiles, comparisons, change feeds, polymarket opportunities, subscriptions, and memory. But relative to the Danish tender scope implied by the server name, only search/detail/recent exist and missing functionality such as saved searches or notifications for new notices. There are also some odd gaps such as no-direct citation-lookup tool, but the generous question-answering tools compensate.

Resources