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Glama

LiveDataLink

by io.github.blackboxfoundry

paper_get_text

Read-onlyIdempotent

Return the full text of an indexed open-access paper by its corpus key (e.g. 'arxiv:2310.12345'), paginated by passage. Use from_seq + max_passages to page through it. For works not indexed locally, returns a pointer to find the open-access URL via paper_search / paper_details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
from_seqNoPassage index to start from (0-based, default 0).
paper_keyYesCorpus key of an indexed paper, e.g. 'arxiv:2310.12345' or 'pmc:PMC1234567'.
max_passagesNoMaximum passages to return per call (default 40, max 200).

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?

Beyond the read-only/idempotent annotations, the description discloses that results are paginated by passage and that non-indexed works yield a pointer to find the open-access URL elsewhere. This adds meaningful behavioral context, though the exact pointer format is not specified.

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 tightly written sentences cover purpose, pagination behavior, and the fallback path without redundancy. The most important information is front-loaded.

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 key-based retrieval tool with strong annotations and full schema coverage, the description is complete. It explains how to page, what happens for non-indexed papers, and where to go for alternatives.

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 the baseline is 3. The description adds value by explicitly linking from_seq and max_passages to the paging mechanism and by giving a realistic corpus key example, going slightly beyond the schema's individual parameter notes.

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 states a specific verb and resource: returning the full text of an indexed open-access paper by corpus key. It clearly distinguishes this retrieval tool from search-oriented siblings by emphasizing key-based lookup and pagination by passage.

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?

The description gives practical usage guidance: use from_seq and max_passages for paging, and explicitly routes the non-indexed case to paper_search / paper_details. It does not directly compare against paper_fulltext_search, leaving some sibling differentiation implicit.

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

B3.3/5.0
Disambiguation2/5

Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.

Naming Consistency3/5

Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.

Tool Count1/5

294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.

Completeness4/5

The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.

Resources