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navjeet4real

context-aware-mcp

by navjeet4real

call_api

Send HTTP requests to a specific service endpoint. Specify service, path, method, headers, body, and environment to call microservices like os-order directly.

Instructions

Direct API call to a specific service endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNo
methodNoGET
headersNo
serviceYes
endpointYesAPI endpoint path
merchantIdNo
environmentNoqa

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. 'Direct API call' at least conveys that an HTTP request is made, but it does not disclose that the tool can perform destructive operations (POST, PUT, DELETE, PATCH) with real side effects, nor does it mention authentication, rate limits, error behavior, or return format. For a tool that can issue arbitrary requests, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single 8-word sentence with zero filler and the purpose front-loaded, which is structurally clean. However, it is under-specified relative to the tool's complexity (7 params, no annotations, no output schema), so brevity crosses into sparse rather than appropriately sized.

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?

This is a high-complexity tool: 7 parameters, no annotations, no output schema, and the ability to issue any HTTP method including destructive ones on arbitrary endpoints. The description gives an agent almost nothing to work with — no guidance on service scope, endpoint discovery (though fetch_swagger exists as a sibling), environment semantics, or side-effect warnings. It is far from complete enough for safe invocation.

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

Parameters2/5

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

Schema description coverage is only 14%, so the description must compensate but barely does. The phrase 'service endpoint' loosely maps to the two required params (service, endpoint), but nothing is said about the roles of merchantId, environment, body, headers, or method semantics. The enums and defaults in the schema carry the real weight; the description adds almost nothing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb+resource: 'Direct API call to a specific service endpoint.' An agent can tell it makes an HTTP request to a named service. However, it does not distinguish itself from the sibling 'smart_api_call' — the word 'Direct' hints at a raw passthrough versus a smarter variant, but this differentiation is never made explicit.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives. The description never mentions smart_api_call, fetch_swagger, or the kafka tools, and gives no conditions for choosing this tool over them. The only implicit signal is the word 'Direct,' which weakly suggests raw calls, but this is not enough to count as implied usage guidance.

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