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regulatory-intel-mcp

regulatory-intel-mcp

by datakoot
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

Agencies

agencies
Read-onlyIdempotent

Look up US federal departments and their slugs to filter regulatory searches by issuing body. Optionally pass a name query like 'environmental' or 'defense'.

Instructions

Look up US federal agencies and their slugs (used to filter the other tools by issuing agency). Optionally pass a query to match by name, e.g. 'environmental' or 'defense'.

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": "agencies"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryNoFilter agencies whose name contains this text.

Output Schema

NameRequiredDescriptionDefault
countNo
sourceNo
agenciesNo
provenanceNoWhere this answer came from. served_at is when Datakoot answered (UTC); upstream lists the official sources consulted. Datakoot may serve a briefly cached copy, so the source's own observation can be older than served_at.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.1.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is fully covered without the description. The description adds the cross-tool context that slugs feed other tools' filters, which is useful, but says nothing about result size, ordering, or auth needs.

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 sentences, zero waste, with the primary purpose and the resource's role front-loaded before the optional parameter detail.

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 an output schema present and rich annotations, the description need not explain return values, and it correctly implies that omitting the query returns the full list. The only marginal gap is that it never states the default behavior explicitly.

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 description coverage is 100% for the single optional parameter, and the schema already states the substring-match semantics. The description's examples ('environmental', 'defense') illustrate but do not materially extend what the schema provides, 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 and resource ('Look up US federal agencies and their slugs') and clarifies the resource's role in the ecosystem as a filter key for other tools. None of the siblings (search_documents, document, recent_documents, executive_orders) is a reference-lookup tool, so the distinction is unambiguous.

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?

Explains the context of use ('used to filter the other tools by issuing agency') and how to narrow results with the optional query. It stops short of explicit when-not guidance or naming a sibling alternative, but the intended workflow is clear.

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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