Skip to main content
Glama
Saikiran2412

RAG MCP Server

by Saikiran2412

retrieve_documents

Retrieve relevant research paper chunks for a query by semantically searching a corpus of arXiv papers. Get top results to answer your question.

Instructions

Retrieve relevant research paper chunks for a query using semantic search over a corpus of arXiv papers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior2/5

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 mentions 'semantic search' which implies relevance-based retrieval, but does not disclose what the output contains (e.g., chunk text, metadata, scores), whether results are sorted, or any limits. For a read operation, it is missing details that would help an agent predict behavior.

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?

The description is a single, concise sentence that front-loads the verb and purpose. Every word contributes value, with no filler or redundancy. It is appropriately sized for a simple retrieval tool.

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

Completeness3/5

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

The tool is simple with two parameters and an output schema, but the description is minimal. It covers the main function but omits any explanation of parameters (especially top_k) and does not mention behavioral nuances like ordering or return format, which are not fully covered by the schema either. It is adequate but leaves gaps.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must explain the parameters. The description implies the 'query' parameter (as it retrieves 'for a query'), but it does not mention 'top_k' at all, nor does it explain how top_k affects the results. Given only two parameters, this is a notable gap.

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 a specific verb ('Retrieve'), a specific resource ('research paper chunks'), and the method ('semantic search over a corpus of arXiv papers'). It is unambiguous and distinguishes the tool from any potential alternative, though no siblings are listed. This is a strong, specific statement of purpose.

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 provides clear context: it is used for semantic search over arXiv papers, which implies when it is appropriate (when dealing with arXiv content). However, it does not explicitly state when not to use it or mention alternatives, but since no siblings exist, this is acceptable. The 'arXiv papers' qualifier serves as a usage guideline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Saikiran2412/Retrieval_MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server