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khushiiagrawal

MCP Research Server

search_papers

Search arXiv papers by topic to retrieve paper IDs and store information locally for organized research management.

Instructions

Search for papers on arXiv based on a topic and store their information.

Args: topic: The topic to search for max_results: Maximum number of results to retrieve (default: 5)

Returns: List of paper IDs found in the search

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It appropriately notes the side effect of storing information and specifies the return value (List of paper IDs), but omits other critical details such as idempotency, what 'store' entails (persistent cache, session memory, etc.), error handling behavior, or rate limiting.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description uses a docstring format with distinct Args and Returns sections. While slightly more structured than typical prose descriptions, it efficiently organizes information with no wasted sentences. The format is machine-parseable and front-loads the core purpose before detailing parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a simple 2-parameter search tool with a straightforward output (list of IDs), the description is adequately complete. It covers the search domain (arXiv), the side effect (storage), and the return type. While additional context on storage scope would be helpful, the description suffices for tool selection and basic invocation.

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?

The input schema has 0% description coverage (only titles). The description compensates via the Args section, documenting both 'topic' (the search query) and 'max_results' (with default value). While it documents the parameters, it lacks rich semantic detail such as expected format for topics, examples, or constraints on max_results.

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 searches for papers on arXiv based on a topic and stores their information. It uses specific verbs ('Search', 'store') and identifies the specific resource (arXiv papers), implicitly distinguishing it from the sibling 'extract_info' tool which likely operates on existing papers rather than searching for them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus the sibling 'extract_info' tool, nor does it specify prerequisites (e.g., whether a topic should be broad or specific) or when not to use it. Agents must infer usage solely from the tool name.

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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