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Execute API Request

execute-request
Destructive

Executes an API request with a given HAR request object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesTitle of the OpenAPI spec. Use tool 'list-specs' or 'search-endpoints' to see available specs.
harRequestYesHAR request object

Schema Changelog

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

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already indicate destructive behavior (destructiveHint: true) and non-read-only status (readOnlyHint: false). The description adds no extra behavioral context, such as side effects on external systems, authentication requirements, or rate limits. It does not contradict annotations, but also does not enrich them.

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 a single, front-loaded sentence that efficiently conveys the core purpose. It contains no fluff or redundant information, and every word contributes to explaining what the tool does.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool executes arbitrary API requests, but the description does not mention what the response looks like, error behavior, or potential side effects beyond what annotations hint. Since there is no output schema, the description should at least indicate that a response is returned. The schema covers parameters, but the overall context for an agent is incomplete.

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%, with detailed descriptions for parameters including the HAR request object's subfields (method, url, postData variants, etc.). The tool description itself adds no parameter-specific meaning, but the schema already provides strong semantics, so a baseline score of 3 is appropriate.

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's function: 'Executes an API request with a given HAR request object.' This uses a specific verb ('executes') and resource ('API request') and distinguishes it from sibling tools that focus on listing/searching endpoints rather than making actual calls.

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 implies the tool is for executing API requests, but it does not explicitly state when to use it versus alternatives. The only related guidance is in the schema's title parameter, which mentions using 'list-specs' or 'search-endpoints' to see available specs—this is more about parameter resolution than tool selection.

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

A4.2/5.0
Disambiguation5/5

Each tool has a clear, distinct purpose: listing specs, listing endpoints, searching endpoints, getting endpoint details, executing requests, and routing operations. Even list-endpoints and search-endpoints are differentiated by organization vs. keyword search, so agents can pick correctly.

Naming Consistency5/5

All tool names follow a consistent verb-noun pattern in snake_case (execute-request, get-endpoint, list-endpoints, list-specs, route-kudosity-operations, search-endpoints). No mixed conventions or vague verbs.

Tool Count5/5

Six tools is well within the ideal range for an API-focused server. Each tool contributes to a clear workflow: discover specs, find endpoints, get details, execute, and plan routing. No redundant or excessive tools.

Completeness5/5

The tool set covers the full lifecycle of API interaction: discovering available specs, locating endpoints, retrieving detailed endpoint info, executing requests, and providing version routing guidance. No obvious gaps for the stated domain.

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