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Glama

Newsapi

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

A4.9/5.0
Behavior5/5

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

Beyond annotations (idempotentHint, non-destructive), the description adds key behavioral details: memory is scoped by identifier, and retention differs for authenticated users (persistent) vs anonymous (24 hours). This is crucial context for an agent deciding whether to rely on the stored data.

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?

Description is compact and well-structured: main action first, then usage trigger, storage semantics, retention policy, and sibling pairing. Every sentence serves a purpose with no 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?

For a simple two-parameter tool with no output schema, the description covers the core purpose, use cases, storage scope, persistence behavior, and integration with related tools. It is sufficiently complete for an agent to decide when and how to invoke it.

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%, so baseline is 3. The description adds value by providing concrete examples (ticker, address, preference) and explaining that entries are stored as a key-value pair scoped by identifier, enriching the purpose of both parameters.

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 clearly states the tool's function with a specific verb ('Save data') and resource ('key-value pair'). It distinguishes from sibling tools recall and forget by explicitly naming them as counterparts for retrieval and deletion.

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?

Provides explicit when-to-use guidance: 'Use when you discover something worth carrying forward...' with concrete examples. It also directs to paired tools (recall, forget) for related operations, effectively indicating when not to use this tool.

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

A3.5/5.0
Disambiguation2/5

There are several clusters of tools with overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions to data sources; entity_profile, compare_entities, and recent_changes all provide company research. The descriptions are detailed, but an agent could easily misselect among these near-duplicates, especially since ask_pipeworx_beta is explicitly identical to ask_pipeworx right now.

Naming Consistency2/5

Placeholder for naming consistency placeholder

Tool Count1/5

34 tools for a server named Newsapi is an extreme scope mismatch. Only three tools (everything, top_headlines, sources) are news-related; the rest cover data research, prediction markets, memory, subscriptions, and package scanning, which belongs in separate servers. The count is also past the 25+ range that feels overloaded for any single purpose.

Completeness3/5

The three NewsAPI tools themselves cover the standard news surface (top_headlines, everything, sources) with no major gaps. However, the server's stated purpose is diluted by ~30 unrelated tools, and the non-news tools form an incoherent assortment with no clear unified domain to assess completeness against. The mismatch makes completeness hard to reason about and degrades the overall usefulness.

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