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ms-methos

jsonfabrica-mcp-server

Create a JsonFabrica batch generation job

jsonfabrica_create_batch

Generate synthetic JSON test data in bulk from templates, with optional relational cross-referencing between documents. Small batches return results immediately; larger ones provide a batch ID to poll.

Instructions

Calls POST /v1/batches. Generates multiple documents from one or more templates in one call, optionally cross-referencing documents via relations. Small batches run synchronously and the response is 200 with results; larger batches are queued and the response is 202 with just { batchId, status, seed } — poll jsonfabrica_get_batch for the final results in that case.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
documentsYes
sequenceNamespaceNo
variableNamespaceNo

Schema Changelog

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

  1. First observedv0.1.4

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the burden, and it reveals important behavior: response differs by batch size (200 with results vs 202 with only batchId/status/seed) and requires polling for larger batches. It also mentions optional relations cross-referencing. It stops short of noting permissions or side effects beyond creation, so not a 5.

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 three-sentence description is tight and front-loaded: endpoint, purpose, then the sync/async split with follow-up action. No filler or repetition.

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 description covers the core request/response lifecycle and even names the polling sibling, which is strong. However, for a 4-parameter tool with nested document objects and 0% schema description coverage, leaving namespace and seed semantics unexplained makes it incomplete for correct 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 0%, so the description must compensate, but it only clarifies `relations` and the response `seed`; it does not explain the `seed` input, `sequenceNamespace`, or `variableNamespace`, nor per-document `alias`, `count`, or `params`. The schema gives types only, so an agent would still guess at key parameter meanings.

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?

Description names the HTTP endpoint and a specific verb ('Generates multiple documents from one or more templates in one call'), making the batch-generation intent unmistakable. It also distinguishes itself from siblings by noting single-call multi-document generation and the polling path via jsonfabrica_get_batch, which separates it from single-document/generation tools.

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?

The description gives concrete context for when the synchronous vs async behavior applies ('small batches run synchronously... larger batches are queued') and tells the agent to poll jsonfabrica_get_batch in the async case. It does not explicitly enumerate when not to use this tool versus generate_adhoc or generate_from_template, but the batch/multi-template framing implies the primary use case.

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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