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'.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Filter agencies whose name contains this text. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden of behavior. It correctly implies a read-only lookup and discloses that results include agencies and slugs, but it does not specify what happens when no query is passed, whether matching is case-insensitive, or the output structure. These are moderate gaps for a simple lookup tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with no wasted words. The core purpose and the optional parameter behavior are both front-loaded, and the examples are directly useful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a single optional parameter and no output schema, the description covers the purpose, the parameter's role, and the kind of data returned (agencies and slugs). It falls slightly short only by not explicitly stating the default behavior when no query is provided, though that is easily inferred from 'optionally'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the query parameter at 100% coverage, so the baseline is 3. The description adds value by explicitly noting the parameter is optional, giving concrete examples ('environmental', 'defense'), and explaining that matching is by agency name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('look up') with a concrete resource ('US federal agencies and their slugs') and explains why they matter ('used to filter the other tools by issuing agency'). This clearly distinguishes it from the sibling document-search tools and tells an agent exactly what the tool provides.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states the primary use case (getting slugs to filter other tools) and explains the optional query behavior. It does not explicitly name sibling tools or give exclusions, but the lookup nature of the tool makes the intended context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct role: agency lookup, single-document retrieval, executive order search, recent document monitoring, and full-text search. The overlap between recent_documents and search_documents is minimal because one is explicitly for monitoring recent publications while the other is for topic-based search.
Tool names are all lowercase and multi-word names use snake_case, which is predictable. Minor deviations exist: 'document' is singular while other resource-oriented names are plural, and 'search_documents' is verb-led while the rest are noun phrases.
Five tools is an appropriate, focused scope for a Federal Register research server. Each tool covers a necessary capability without redundancy or bloat.
The tool surface covers the core workflow: discover documents via search or recent listings, retrieve full details by document number, filter by agency, and access executive orders. There are no obvious dead ends for the stated regulatory intelligence purpose.