IDX MCP - Indonesia Stock Exchange Trading Data

Idx_market_summary

Read-only

Whole-market snapshot for one trading day: every ticker that traded, joined with its company name and sector. Use it for top gainers/losers (sortBy changePercent), most active (value, volume, frequency) and foreign flows (foreignNet). Defaults to the latest trading day; a date with no trading (weekend, holiday) returns no rows.

Filter by sector/industry substring, a list of codes, or minimum traded value.

Prices (previous, openPrice, high, low, close, change, bid, offer) are IDR per share. volume, listedShares, tradeableShares, foreignBuy and foreignSell are shares; value is IDR; frequency is the number of trades. changePercent = change / previous × 100 and foreignNet = foreignBuy − foreignSell are computed.

Returns { date, data, total, page, limit }.

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": "Idx_market_summary"
  }
}

Input Schema

Name	Required	Description	Default
`date`	No	Trading day, YYYY-MM-DD. Defaults to the latest.
`page`	No
`codes`	No
`limit`	No
`sector`	No
`sortBy`	No		value
`industry`	No
`minValue`	No	Minimum traded value, IDR.
`sortOrder`	No		desc

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 30, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already cover the read-only/safe profile, and the description adds substantial extra context: defaulting to the latest trading day, that weekends/holidays return no rows, and a full unit map (IDR for prices/value, shares for volume/listedShares/foreignBuy/foreignSell, trade counts for frequency). It also discloses which fields are computed (changePercent, foreignNet), which goes well beyond the structured data.

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?

Front-loaded with the purpose and use cases, followed by filter semantics, then units, then the return shape. Every sentence adds information an agent needs; no filler.

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

Completeness5/5

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

No output schema exists, but the description supplies the return shape ({ date, data, total, page, limit }), the pagination-relevant fields, unit conventions, and edge-case behavior for non-trading days. Nothing material is missing for correct invocation.

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

Parameters5/5

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

Schema description coverage is only 22%, so the description carries the burden and does: it explains that sector/industry are substring filters, codes accepts a list of ticker codes, minValue sets a minimum traded value, and sortBy accepts changePercent/value/volume/frequency/foreignNet. Only page/limit lack prose, and their defaults are already in the schema.

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+resource ('whole-market snapshot for one trading day') with scope ('every ticker that traded, joined with its company name and sector'), which clearly distinguishes it from the company-level siblings (Idx_get_company, Idx_price_history). An agent can identify the tool without opening the schema.

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

Usage Guidelines4/5

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

Gives concrete use cases mapped to sortBy values (top gainers/losers via changePercent, most active via value/volume/frequency, foreign flows via foreignNet) plus the default behavior and the empty-result edge case for non-trading days. It does not explicitly name an alternative sibling tool or state when not to use this one, so it falls short of 5.

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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