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sanjeev0291

nse-research-mcp

by sanjeev0291

search_stocks

Search NSE stocks by company name or partial symbol to retrieve symbol, ISIN, listing date, industry, and index membership.

Instructions

Find NSE symbols by company name or partial symbol (e.g. "tata motors", "hdfc", "INFY"). Returns symbol, name, ISIN, listing date, NSE industry and index membership (NIFTY 50/500 etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral transparency burden. It usefully discloses NSE scope and return fields, but it does not explain search behavior such as case sensitivity, partial vs exact matching, handling of multiple matches, or empty result 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 concise, front-loads the core purpose, and uses concrete examples to illustrate valid inputs. The second sentence succinctly lists the expected return fields without unnecessary filler.

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?

For a simple lookup tool with one required parameter, the description plus schema is largely sufficient to invoke it correctly. The main gap is the lack of explicit limit semantics, but the default value and parameter name make it reasonably inferable. The presence of an output schema also reduces the need to describe return values in detail.

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 compensate for both parameters. It adds meaning to 'query' by explaining that it accepts company names or partial symbols, but it says nothing about 'limit' beyond what the parameter name and default value already imply.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Find NSE symbols by company name or partial symbol.' It provides concrete examples and enumerates return fields (symbol, name, ISIN, listing date, industry, index membership), making the tool's role clear. However, it does not explicitly distinguish itself from sibling tools like screen_stocks or get_company_profile.

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

Usage Guidelines3/5

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

The description clearly implies a lookup use case: finding NSE symbols by company name or partial symbol. It does not explicitly state when to prefer this tool over alternatives like screen_stocks or get_company_profile, nor does it mention exclusions such as unsupported exchanges or exact-match requirements.

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