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Glama

Nasa

by io.github.pipeworx-io

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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 indicate idempotence and non-destructiveness. Description adds key behavioral details: scoped by identifier, authentication-based persistence (persistent vs 24-hour TTL), and storage as key-value pair. No contradictions 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?

Four tight sentences front-loading purpose, followed by usage context, behavioral details, and tool pairing. No wasted 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?

For a simple 2-param tool with no output schema, the description fully covers purpose, usage patterns, persistence details, and relationships to sibling tools. Complete and self-contained.

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 covers both parameters with descriptions. Description adds real-world examples (ticker, address, preference) and clarifies value is free text, enhancing the schema's explanation.

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?

Description clearly states 'Save data the agent will need to reuse later', specifying a verb (save) and resource (key-value pair). It distinguishes from sibling tools like recall and forget, which are retrieval and deletion respectively.

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?

Provides explicit when-to-use: 'when you discover something worth carrying forward'. Mentions pairing with recall and forget, but does not explicitly exclude scenarios like transient data requiring no persistence.

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

A3.7/5.0
Disambiguation2/5

Several tools occupy nearly identical semantic space: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded all route through the same 5,798 tools and differ mainly in output strictness or testing status. The Polymarket cluster also has significant boundary overlap, and the 'Nasa' server name makes the large block of unrelated data tools even more confusing to navigate.

Naming Consistency4/5

Most tools follow a clear verb_noun snake_case pattern (get_apod, search_nasa_images, resolve_entity, validate_claim, unsubscribe), and family prefixes like ask_pipeworx and polymarket_ are consistent. A few noun-first outliers like entity_profile, deep_research, and bet_research break the pattern slightly, but the overall style is still readable and predictable.

Tool Count2/5

With 36 tools, this set is well beyond the comfortable 3-15 range and even exceeds the 16-25 'heavy' band. Only about five tools actually relate to the server's apparent NASA identity, while the rest form a general data/Pipeworx utility kit that would be better split into a separate server.

Completeness2/5

For a server named 'Nasa,' the surface is thin: APOD, asteroids, Mars rover photos, solar flares, and image search cover only a slice of NASA's API portfolio, with no launch schedules, Earth imagery, mission/news feeds, or ISS data. The general Pipeworx tools make the server broad but incoherent, and a user focused on NASA would hit dead ends quickly.

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