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Indian Stock Exchange API2 MCP Server

Indian Stock Exchange API2 MCP Server

by BACH-AI-Tools
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

industry_search

Search for Indian companies by industry name to identify stocks within specific sectors on NSE and BSE exchanges.

Instructions

$23b

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "industry_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesExample value: tata

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

D1.4/5.0
Behavior1/5

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, yet '$23b' reveals nothing about whether this is read-only, what data sources it queries, rate limits, or whether results are cached or real-time.

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

Conciseness2/5

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

While extremely brief, '$23b' represents under-specification rather than purposeful conciseness. It contains no actionable information and fails to front-load any meaningful guidance about the tool's function.

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

Completeness1/5

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

Given the lack of annotations, absence of output schema, and the presence of numerous financial search siblings, the tool requires descriptive context to distinguish its purpose. The description fails completely to explain what constitutes an 'industry' in this context or what data is returned.

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?

With 100% schema description coverage (the 'query' parameter includes an example value 'tata'), the baseline score is 3. The description adds no semantic value regarding what the query should contain (e.g., industry names vs. codes), but the schema sufficiently documents the input format.

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

Purpose1/5

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

The description '$23b' is not descriptive text at all; it appears to be a data value or placeholder that erroneously replaced the actual description. It fails to state what the tool searches for, what 'industry' refers to (sectors, classifications, etc.), or what the return data represents.

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

Usage Guidelines1/5

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

There is zero guidance on when to use this tool versus siblings like 'mutual_fund_search' or 'get_stock_data_by_name'. The description provides no context about the search scope or prerequisites.

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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