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dataville-mcp

by datavilleorg

Describe a Dataville data source

describe_dataville_source
Read-onlyIdempotent

Shows how to use a Dataville data source: required search keywords with an example, plus SQL tables and columns available for queries. Sources without tables support search only.

Instructions

Show how to use one data source: what search_dataville expects as keywords (with an example that returns a result), and the SQL tables and columns query_dataville can read for it. Sources with no tables can only be searched.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYesData source name from list_dataville_sources, e.g. 'edgar'

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.8

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, destructiveHint=false, so the safety profile is covered. The description adds behavioral context about the payload (keyword example that returns a result, available tables/columns) and the read-only-search-only limitation. Useful but not rich beyond the annotations.

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 tight sentences with a compact parenthetical, front-loading what the tool shows. Every clause carries information; nothing is wasted.

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?

With no output schema, the description carries the burden of explaining the return contents and does so by naming the three payload categories (search keywords + example, tables, columns) and the no-tables limitation. It could say more about output structure/format, but it is sufficient for an agent to use the result.

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?

A single parameter with 100% schema description coverage; the schema already explains 'source' comes from list_dataville_sources with an example. The description adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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 (describe one data source) and details exactly what it returns: search_dataville keyword expectations with an example, plus the SQL tables/columns query_dataville can read. It is clearly demarcated from the sibling search/query/list tools by naming them.

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?

By explaining that it reveals what search_dataville expects and what query_dataville can read, it implies this is the prerequisite reconnaissance call before those tools. It also notes a usage constraint ('sources with no tables can only be searched'). It stops short of an explicit 'call this before X' directive, so not a full 5.

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