JobNimbus MCP Server

by drummouse

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TypeScript

Local

jn_create_job

Create a new job in JobNimbus with customizable fields including lead and job numbers from GHL via custom_fields_json.

Instructions

Create a new job in JobNimbus. Pass GHL Lead Number and Job Number via custom_fields_json.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "jn_create_job"
  }
}

Input Schema

Name	Required	Description
`zip`	No
`city`	No
`name`	Yes	Job name/title
`tags`	No
`geo_lat`	No	GPS latitude
`geo_lon`	No	GPS longitude
`state_text`	No
`description`	No
`status_name`	No
`contact_jnid`	No	jnid of the related contact
`address_line1`	No
`custom_fields_json`	No	JSON string of custom fields, e.g. {"Lead Number":"L-001","Job Number":"J-001","Plus Code":"XXXX+XX"}

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 9, 2026

TDQS

B3.2/5.0

Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It states the tool creates a job (mutation) but omits any side effects, authorization requirements, idempotency, or error conditions. This is a significant gap for a creation tool.

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 a single sentence that efficiently conveys the core purpose. It is front-loaded with the main action. However, it could add more detail without becoming verbose, as it currently omits important usage context.

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?

Given 12 parameters, low schema coverage, no output schema, and no annotations, the description is insufficient. It does not explain required fields beyond name, the creation process, or what the response contains, leaving the agent underinformed.

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 coverage is 42% (low), and the description only clarifies the custom_fields_json parameter by specifying the GHL Lead Number and Job Number fields. Other parameters like zip, city, tags, and state_text are left unexplained, failing to compensate for the low schema coverage.

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 creates a new job in JobNimbus, specifying the resource (job) and action (create). It distinguishes from sibling tools like jn_list_jobs and jn_update_job, and the mention of custom_fields_json highlights a key use case.

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 usage for creating jobs with specific custom fields (GHL Lead Number and Job Number), but it provides no explicit guidance on when not to use this tool or alternatives (e.g., jn_create_contact for contacts). The context is clear but lacks exclusion criteria.

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