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Glama

Conceptnet

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

A4.9/5.0
Behavior5/5

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

Adds significant context beyond annotations: scoping by identifier, persistence differences (authenticated vs anonymous), 24-hour retention for anonymous, and cross-session use. 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?

Two compact sentences front-loaded with purpose and usage, followed by essential behavioral details. No extraneous words.

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?

Fully covers purpose, usage, behavior, parameter hints, and tool relationships. Given two simple parameters, no output schema, and rich annotations, no gaps remain.

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% with descriptions for both parameters. Description adds naming conventions (e.g., 'subject_property') and usage context, providing slight additional value beyond schema.

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?

Clearly states 'Save data the agent will need to reuse later' with specific examples (resolved ticker, target address, user preference) and distinguishes from siblings recall and forget.

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 instructs when to use ('when you discover something worth carrying forward') and pairs with recall/forget, providing clear usage context and alternatives.

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

All Conceptnet toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical, and the five polymarket_* tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) all target prediction-market opportunities. The memory tools (remember/recall/forget) are distinct, as are subscriptions, but the routing and Polymarket clusters create real misselection risk.

Naming Consistency3/5

All names are snake_case, but the pattern is mixed: some are verb_noun (ask_pipeworx, compare_entities, discover_tools, resolve_entity), some are noun_verb or adjective_noun (bet_research, entity_profile, pipeworx_trending, recent_changes), and some are bare nouns/verbs (lookup, query, recall, relatedness). The 'polymarket_*' and 'ask_pipeworx*' families are consistent internally, but the overall set lacks a uniform verb-first convention.

Tool Count2/5

With 34 tools, the server is heavily over-scoped for a server named 'Conceptnet' — the vast majority of tools belong to a separate Pipeworx data-access product, not a semantic-network API. While each tool has a use, the count feels bloated and the server name misrepresents the actual surface.

Completeness4/5

The ConceptNet portion is complete (lookup, query, relatedness cover graph traversal). The Pipeworx portion is also fairly complete: universal router, grounded mode, deep research, entity profiles, comparisons, claim validation, subscription lifecycle, memory, and feedback. Minor gaps exist (e.g., no direct SEC filing fetch without going through ask_pipeworx), but the meta-tools mostly fill them.

Resources