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aswathas

TradeMCP

by aswathas
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

trademcp_screen_stocks

Read-onlyIdempotent

Screen Indian stocks by fundamental and technical criteria across NIFTY or NSE universes. Filter by valuation, profitability, growth, debt, RSI and moving averages, then return matching stocks.

Instructions

Screen Indian stocks by fundamental and technical criteria.

Scans an index universe (or every NSE-listed stock), pulls the latest fundamentals for each name, applies the fundamental filters, then applies the technical filters to the survivors and returns the best matches.

Args: universe: 'NIFTY 50', 'NIFTY 100', 'NIFTY 500' or 'NSE' min_pe: maximum P/E max_pe: minimum P/E min_roe: minimum return on equity (%) min_roce: minimum return on capital employed (%) min_net_margin: minimum net margin (%) max_debt_to_equity: maximum debt/equity min_market_cap: minimum market cap in rupees min_dividend_yield: minimum dividend yield (%) min_current_ratio: minimum current ratio min_revenue_cagr: minimum 3-year revenue CAGR (%) rsi_below: maximum RSI (oversold screen) rsi_above: minimum RSI (overbought screen) above_sma50: require price above the 50-day average above_sma200: require price above the 200-day average limit: maximum rows to return sort_by: field to sort by sort_order: 'desc' (default) or 'asc' response_format: 'markdown' or 'json'

Returns: Markdown table or JSON with 'matches' and the filter set applied.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum stocks to return (1-100)
max_peNoOnly stocks with P/E at or above this
min_peNoOnly stocks with P/E at or below this
min_roeNoMinimum return on equity (%)
sort_byNoSort field: 'market_cap', 'pe_ratio', 'price_to_book', 'roe_pct', 'roce_pct', 'revenue_cagr_3y_pct', 'dividend_yield_pct', 'health_score'market_cap
min_roceNoMinimum return on capital employed (%)
universeNoStock universe to scan: 'NIFTY 50', 'NIFTY 100', 'NIFTY 500' or 'NSE' (all listed)NIFTY 50
rsi_aboveNoOnly stocks with RSI over this (overbought screen)
rsi_belowNoOnly stocks with RSI under this (oversold screen)
sort_orderNoSort direction: 'desc' or 'asc'desc
above_sma50NoOnly stocks trading above their 50-day average
above_sma200NoOnly stocks trading above their 200-day average
min_market_capNoMinimum market cap in rupees
min_net_marginNoMinimum net profit margin (%)
response_formatNo'markdown' or 'json'markdown
min_revenue_cagrNoMinimum 3-year revenue CAGR (%)
min_current_ratioNoMinimum current ratio
max_debt_to_equityNoMaximum debt to equity ratio
min_dividend_yieldNoMinimum dividend yield (%)

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive and open-world, so safety is covered. The description adds real behavioral detail beyond that: the two-stage filter order (fundamentals first, technicals on survivors) and that both matches and the applied filter set are returned. It omits expected latency/result-size implications of scanning the full NSE universe.

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?

The opening paragraph is well front-loaded and earns its place. However, the 19-line Args block restates parameters that are already 100% documented in the schema, adding bulk without new meaning.

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?

Output schema exists and annotations cover safety, so the description need only explain the process — which it does. The main residual gap is the ambiguous P/E parameter wording and the absence of any note on scan cost/results for large universes.

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 coverage is 100%, so baseline would be 3, but the description actively muddles two parameters: it says 'min_pe: maximum P/E' and 'max_pe: minimum P/E', which conflicts with the schema's own (already inverted-looking) descriptions. An agent reading both would have to guess the direction of the P/E filter, which is a real error risk.

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

Purpose5/5

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

States a specific verb and resource ('Screen Indian stocks by fundamental and technical criteria') and the pipeline (index/NSE scan → fundamentals → technical filters). Among siblings that fetch single-company data, this is clearly the only multi-name screening tool, so differentiation is immediate.

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?

Usage is implied by the description's screening framing, but there is no explicit statement of when to reach for this instead of get_fundamentals or compare_stocks, and no guidance on universe cost trade-offs (e.g., 'NSE' scans everything).

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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