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jsonfabrica-mcp-server

Create a JsonFabrica template

jsonfabrica_create_template

Create reusable templates from function-call placeholders to generate realistic JSON test data on demand, or produce a sample document immediately in the same call.

Instructions

Calls POST /v1/templates. Creates a reusable template. body uses JsonFabrica's function-call placeholder syntax, e.g. "Hello {{getRandomFullName()}}" or "<getRandomNumber(1,100)>" — see the data-generation-functions reference for the full catalog. If generate is provided, a document is generated from the newly-created template in the same call (response includes generation or generationError alongside template); if omitted, the response is just the created template.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesTemplate body containing at least one function-call placeholder.
nameYesTemplate name.
tagsNo
generateNo
descriptionNo

Schema Changelog

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

  1. First observedv0.1.4

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses the HTTP call, the response shape when generate is provided vs omitted, and documents the placeholder syntax with examples. It does not mention error conditions, authentication, or idempotency, but the create semantics are straightforward.

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

Conciseness4/5

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

The description is compact and front-loads the endpoint and core action, then explains the placeholder syntax and the conditional behavior of generate. The examples and conditional explanation are valuable, but the sentence is long and could be split for easier scanning.

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?

Given the nested generate object and no output schema, the description covers the most important context: endpoint, placeholder syntax, and the two distinct request/response modes. It lacks an example of a full request object and does not explain tags, but the core usage is sufficiently complete for an agent to invoke creation correctly.

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 coverage is 40%, and the description adds meaning for body and generate, including examples of placeholder syntax and the shape of the response. However, it does not add semantics for name, tags, or description beyond what the schema provides, and the generate object's seed/params/context fields rely fully on the schema.

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 explicitly names the HTTP endpoint (POST /v1/templates), the verb (creates), the resource (a reusable template), and the key behavior (reusable template with placeholder syntax). It differentiates from siblings like generate_from_template and update_template by framing creation specifically.

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?

It clearly states when to use this tool: to create a template, with an optional same-call generation. It does not explicitly name alternatives like update_template or generate_from_template, but the purpose is distinct enough that an agent can infer when to choose it. The optional generate behavior is clearly explained.

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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