Indian Stock Exchange API2 MCP Server

nse_most_active

Retrieve current most actively traded stocks on India's National Stock Exchange based on trading volume data for market analysis.

Instructions

NSE Most Active Endpoint: `/NSE_most_active` Method: GET Description: Get the latest most active stocks in the National Stock Exchange (NSE) based on trading volume. Example Request: `http GET /NSE_most_active` Example Response: ```json [ { \

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "nse_most_active"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Implementation Reference

server.py:56-61 (handler)
The tool 'nse_most_active' is automatically registered by FastMCP using the provided OpenAPI specification in `OPENAPI_SPEC`. The handler for the tool is dynamically generated based on the OpenAPI 'operationId' mapping to the corresponding path in the API.
```
mcp = FastMCP.from_openapi(
    openapi_spec=openapi_dict,
    client=client,
    name="indian_stock_exchange_api2",
    version=__version__
)
```

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Mar 25, 2026

TDQS

B3/5.0

Behavior2/5

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

With no annotations provided, the description carries the full disclosure burden. It mentions the GET method and 'latest' data (implying real-time/recent), but lacks critical behavioral details: rate limits, what constitutes 'most active' (top N count?), pagination behavior, market hours relevance, or safety guarantees. The truncated example response is cut off mid-JSON, reducing utility.

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

Conciseness3/5

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

Markdown formatting with endpoint/method headers adds structural clarity but also verbosity. The core description is one clear sentence. However, the included example response is truncated/malformed (ending with escaped quotes), which wastes space and creates visual noise without adding value.

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?

Adequate for a zero-parameter retrieval tool. It identifies the exchange (NSE) and metric (volume), but given the lack of output schema, the truncated example JSON could have provided critical field documentation if complete. Missing operational context like data freshness guarantees or rate limiting.

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?

Input schema has zero parameters (100% coverage trivially satisfied). The description correctly implies this is a parameterless fetch operation requiring no filters, meeting the baseline expectation for zero-parameter tools.

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 states the verb (Get), resource (most active stocks), and scope (NSE based on trading volume). It implicitly distinguishes from sibling 'bse_most_active' by specifying the National Stock Exchange, though it doesn't explicitly differentiate from 'get_trending_stocks' or 'price_shockers'.

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?

No explicit guidance on when to use this tool versus siblings like 'bse_most_active' or 'get_trending_stocks'. While the NSE naming provides implicit context, there are no stated prerequisites or exclusion criteria for selection.

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

Deploy Server