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siddharthgaur1

indian-markets-mcp

NSE index constituents

nse_index_constituents
Read-onlyIdempotent

Retrieve the constituent stocks of any NSE index, such as NIFTY 50 or NIFTY BANK, with company name, industry, symbol, series, and ISIN from official index data. Note: constituent weights are not available.

Instructions

Constituent stocks of an NSE index (e.g. 'NIFTY 50', 'NIFTY BANK'), from the CSV that NIFTY Indices publishes. Returns company name, industry, symbol, series and ISIN. CONSTITUENT WEIGHTS ARE NOT AVAILABLE — NSE publishes them only in factsheet PDFs and a paid product, so do not infer or estimate them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexYesIndex name, e.g. 'NIFTY 50', 'NIFTY IT'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotent annotations, the description adds valuable behavioral context: the data source is a NIFTY Indices CSV, and critically, constituent weights are not available and must not be inferred or estimated. This is actionable and prevents a common misuse.

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 compact and front-loaded: it states the core functionality and returned fields first, then adds the critical weight-availability warning. Every sentence earns its place, and there is no redundant 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 one-parameter read-only tool, the description is nearly complete: it names the output fields and the major constraint (no weights). The only notable gap is not pointing to list_nse_indices as the way to enumerate valid index names, though the examples and schema partially mitigate this.

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

Parameters3/5

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

Schema coverage for the single parameter is 100%, with the schema already specifying 'Index name' and examples. The description contributes an additional example ('NIFTY BANK') and clarifies the NSE context, but it does not add substantial semantic meaning beyond the schema.

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 clearly identifies the resource ('constituent stocks of an NSE index') and the fields returned (company name, industry, symbol, series, ISIN). It lacks an explicit action verb like 'fetch' or 'list' and does not explicitly differentiate from sibling tools, so it is clear but not maximally distinctive.

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 implies when to use the tool: when you need the constituent stocks of an NSE index. However, it provides no explicit when-not-to-use guidance and does not mention alternatives such as list_nse_indices for discovering available index names or nse_eod_quote/history for price data.

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