mcp-server-worldquantbrain

Overview Schema Source Related Servers Discussions Admin

List datasets

list_datasets

Read-onlyIdempotent

Retrieve datasets available for a market, filtering by region, universe, category, theme, delay, and order to select data for alpha research.

Instructions

List datasets available for a market. Cached for a day.

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": "list_datasets"
  }
}

Input Schema

Name	Required	Description
`delay`	No	Data delay, 0 or 1.
`limit`	No
`order`	No	e.g. -coverage or -valueScore.
`theme`	No
`offset`	No
`region`	No	Market region, e.g. USA. Empty uses the default.
`search`	No
`category`	No	Category id from list_data_categories.
`universe`	No	Universe, e.g. TOP3000. Empty uses the default.
`instrument_type`	No	EQUITY unless configured otherwise.

Output Schema

Name	Required	Description	Default
`count`	No
`items`	No
`next_offset`	No
`truncated_by_api`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 11, 2026

TDQS

B3.3/5.0

Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds one genuinely useful behavioral fact not present in structured data — results are cached for a day, implying stale data. It omits pagination behavior (limit/offset exist) and how defaults are applied when region/universe are empty.

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?

Two short sentences, front-loaded with the resource and immediately followed by the caching caveat. Zero filler and nothing that could be trimmed without losing information.

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?

Rich annotations plus an output schema reduce the burden, but for a 10-parameter, paginated list tool the description should at least signal paging and the default-vs-explicit region/universe semantics. The caching note is the only value-add beyond structured fields.

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?

Schema coverage is 60% across 10 optional parameters; the schema already documents delay, order, region, category (with a pointer to list_data_categories), universe and instrument_type. The description adds no parameter meaning at all, and undocumented items such as theme, search, limit and offset rely purely on schema titles.

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?

States a specific verb and resource ('List datasets') plus a scope qualifier ('available for a market'), so an agent knows it enumerates datasets rather than fetching one. It does not, however, distinguish itself from siblings such as get_dataset, list_datafields or list_data_categories, leaving the list-vs-get choice to inference.

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?

The only guidance is 'Cached for a day'; there is no statement of when to reach for this tool versus get_dataset (single lookup) or list_datafields (columns within a dataset). Nothing tells the agent about prerequisites such as authentication or the default region/universe behavior.

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