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Glama

iplookup

by io.github.pipeworx-io

Recall

recall
Read-onlyIdempotent

Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoMemory key to retrieve (omit to list all keys)

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "key": "user_research_topic"
+  },
+  {}
+]
  2. Added

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds valuable context by explaining the tool is 'Scoped to your identifier (anonymous IP, BYO key hash, or account ID)' and that omitting the key lists all saved keys, which goes beyond the schema. No contradiction with 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, with the core action in the first sentence, usage context in the second, and scoping/relationships in the third. Every sentence contributes distinct value with no repetition or fluff.

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?

The tool is simple (one optional parameter, no output schema) and the description covers both modes (retrieve by key, list all), the intended use case, scoping details, and companion tools. This is complete for an agent to select and invoke the tool correctly.

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 coverage is 100% for the single key parameter, and the schema describes it as 'Memory key to retrieve (omit to list all keys)'. The description reinforces this by explaining the omit-to-list behavior and clarifying that the key must have been previously saved via remember, adding semantic meaning beyond the schema's field description.

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 'Retrieve a value previously saved via remember, or list all saved keys (omit the key argument)', which is a specific verb+resource combination and explicitly distinguishes from sibling tools like remember (save) and forget (delete). It also provides concrete examples of stored context (ticker, address, research notes), making the purpose unambiguous.

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?

The description states 'Use to look up context the agent stored earlier ... without re-deriving it from scratch', giving a clear reason to invoke this tool. It also says 'Pair with remember to save, forget to delete,' which explicitly names complementary alternatives and how they fit together, making usage conditions clear.

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

All iplookup toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Several tool families have genuine boundary ambiguity: ask_pipeworx and ask_pipeworx_beta are currently identical in behavior, and the five Polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) all live in the 'find/pursue an edge' space, requiring an agent to parse very long descriptions to choose correctly. The IP, memory, and subscription tools are clearly distinct, but the overlap-prone families cause real misselection risk.

Naming Consistency3/5

All names are snake_case and each family is internally consistent (polymarket_*, ask_pipeworx_*, subscribe/unsubscribe, remember/recall/forget). However, conventions mix across the set: verb_noun (geolocate_ip, resolve_entity, validate_claim) coexists with noun-first names (entity_profile, pipeworx_feedback, recent_alerts) and bare verbs (remember, forget), so there is no predictable global pattern.

Tool Count2/5

At 33 tools the set exceeds the heavy threshold, and the server name 'iplookup' covers only 2 of them; the remaining 31 form a sprawling data-research, prediction-market, memory, and subscription platform with tangential utilities like generate_llms_txt and scan_dependency. The broad scope means few tools are individually useless, but the server reads as a kitchen sink rather than a focused toolkit.

Completeness3/5

As an IP-lookup service the surface is thin: only geolocation and ISP data, with no WHOIS, reverse DNS, proxy/VPN detection, or reputation records. As a data-research platform the surface is strong (universal query routing, grounded verification, entity profiles, comparisons, subscription lifecycle, memory). This lopsidedness makes the actual domain ambiguous and leaves the namesake use case under-covered.

Resources