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Glama

Jwt

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. First observed

TDQS

A4.8/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true and idempotentHint=true. Description adds behavioral details: omitting key lists all keys, scoped to identifier, and pairing with siblings. 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?

Four sentences, each with distinct value: core function, usage context, scoping, and relationships. No redundant phrases.

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?

For a simple tool with one optional parameter and full annotations, the description covers purpose, usage, scoping, and sibling relationships comprehensively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and description adds critical meaning: omitting the key parameter lists all saved keys, which is not in the schema's 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 uses specific verbs 'retrieve' and 'list', identifies resource 'value previously saved via remember' and 'all saved keys', and distinguishes from sibling tools like remember 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 states when to use: 'Use to look up context the agent stored earlier... without re-deriving it from scratch.' Mentions scoping and pairs with remember/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 Jwt toolsInspect
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TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools have unclear boundaries. ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route natural-language queries to the same underlying catalog, with ask_pipeworx_beta currently documented as identical to ask_pipeworx. The Polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk) also overlaps in purpose, leaving an agent to parse fine-grained differences before selecting.

Naming Consistency3/5

All tool names use snake_case and several share recognizable prefixes (ask_pipeworx_*, polymarket_*), which helps readability. However, the verb/noun order is inconsistent—compare_entities vs entity_profile, bet_research vs deep_research, scan_competitor_ai_presence vs ai_visibility_check—and bare verbs like remember, forget, and subscribe mix with noun-first names.

Tool Count2/5

32 tools is well above the 25-tool threshold for a coherent set. The bloat is worse because the server is named 'Jwt' but only one tool relates to JWT; the rest cover unrelated domains such as data routing, prediction markets, memory, subscriptions, and npm scanning, so the count is neither scoped to the server's name nor internally cohesive.

Completeness2/5

For a server named 'Jwt', the surface is severely incomplete: only decode_jwt is present, with no sign, verify, encode, or refresh tools, so common JWT workflows dead-end. Even when judged as a general Pipeworx data toolkit, the mismatch between the server name and the actual tool surface creates a significant gap for agents expecting JWT functionality.

Resources