Indian Stock Exchange API2 MCP Server

get_stock_data_by_name

Retrieve detailed stock information for Indian companies by entering the company name. Access current prices, historical data, and market statistics from NSE and BSE exchanges.

Instructions

$23a

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": {
      "name": "<name>"
    },
    "name": "get_stock_data_by_name"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes	Example value: tata steel

Implementation Reference

server.py:56-61 (handler)
The "get_stock_data_by_name" tool is automatically generated by FastMCP.from_openapi from the OpenAPI specification defined in the OPENAPI_SPEC constant.
```
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

D1.3/5.0

Behavior1/5

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

No annotations are provided, so the description must carry the full burden of disclosing behavioral traits (side effects, rate limits, data freshness). The '$23a' placeholder reveals nothing about whether this is a read-only operation, if it requires API keys, or what volume of data is returned.

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

Conciseness1/5

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

While '$23a' is brief, it represents under-specification rather than effective conciseness. The description fails to front-load any meaningful information and does not earn its place as valid documentation.

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 complexity of stock data retrieval and lack of output schema, the description should explain what data points are returned (price, volume, P/E, etc.). The placeholder '$23a' provides no indication of the tool's scope or return values, making it completely inadequate.

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?

The input schema has 100% description coverage (the 'name' parameter includes an example value 'tata steel'). With high schema coverage, the baseline score is 3 even though the description '$23a' adds no semantic value regarding the parameter.

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 '$23a' is meaningless placeholder text that fails to state what the tool does. It does not mention retrieving stock data, financial information, or any specific verb and resource combination. The name 'get_stock_data_by_name' implies the function, but the description itself provides zero informational value.

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 no guidance on when to use this tool versus its 15 siblings (such as historical_data, analyst_recommendations, or price_shockers). The placeholder '$23a' offers no context about whether this returns real-time vs. delayed data, fundamental vs. technical data, or how it differs from other data retrieval tools.

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

Deploy Server