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Routebase

by dev.routebase.mcp

List Header Components

list_header_components
Read-only

List the header components defined at one level: 'spec' (needs specId) or 'project'. Set includeUsageCounts to see how often each is referenced — spec level only. Returns the ids and rowVersions needed to change them or assign them in a header policy. Requires project context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
levelYesWhich level to read: 'spec' or 'project'
specIdNoPublic ID (GUID) of the API specification — required for level 'spec'
versionIdNoOptional version ID (GUID) to filter by a specific version — spec level only
includeUsageCountsNoAlso return how often each component is referenced — spec level only (default false)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The description adds behavioral details beyond the readOnlyHint annotation: it notes the requirement for project context, that includeUsageCounts is spec-level only, and that the return includes ids and rowVersions. It does not contradict the annotation.

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?

The description is concise, front-loaded with the main action, and clearly structured. It avoids unnecessary detail and gets to the point efficiently.

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?

The description adequately covers what the tool returns (ids and rowVersions) and notes the required context. It lacks an explicit statement about output shape or error scenarios, but for a simple list tool with no output schema it is sufficiently complete.

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

Parameters4/5

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

Despite 100% schema coverage, the description adds valuable conditional semantics for parameters: specId is required if level is 'spec', versionId and includeUsageCounts apply only at spec level. This clarifies the interplay between parameters and the level value.

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?

The description clearly states the tool lists header components at a specified level ('spec' or 'project'), and mentions it returns ids and rowVersions. This is specific and distinct from sibling tools like get_header_component.

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

Usage Guidelines3/5

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

The description provides some usage guidance (requires project context, specId needed for spec level, includeUsageCounts only for spec), but it does not explicitly contrast with alternative tools like get_header_component or list_header_policies. More explicit when-to-use versus alternatives would be helpful.

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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TDQS

A3.9/5.0
Disambiguation4/5

The tools are mostly distinct with clear descriptions. Some pairs like get_header_policies vs get_resolved_headers or get_environment_verification vs get_monitoring_sync_status could be slightly confusing, but the descriptions clarify scope and purpose.

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern (get_, list_, create_, update_, manage_, etc.). Even the few bare verbs like 'search' and 'set_context' are consistent with the naming scheme.

Tool Count1/5

With 165 tools, the server is extremely heavy. This far exceeds the 'too many' threshold of 25+, making it difficult for an agent to navigate and select the right tool efficiently.

Completeness5/5

The tool surface covers a very broad API lifecycle domain: specs, environments, test cases, monitors, mock servers, security, governance, documentation, and team management. Read and write operations are present across most areas, with no obvious missing core functionality.

Resources