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Accelo MCP by usefulapi

Create a company

create_company
Destructive

MUTATES Accelo data: creates a new company (client organization). Accelo API: POST /api/v0/companies (form-encoded). Returns { meta, response } with the created company. (Accelo has no separate delete tool here; to UPDATE, POST to /api/v0/companies/{id}.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesCompany name (required).
phoneNoPrimary phone number.
fieldsNoAdditional documented Accelo fields to send in the write body (merged with the typed fields above).
websiteNoCompany website URL.
commentsNoFree-text comments/notes on the company.
status_idNoCompany status id (from your deployment's company statuses).

Schema Changelog

Changes observed during successful MCP inspections.

  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

A4.1/5.0
Behavior4/5

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

Discloses behavior beyond the annotations: it names the exact endpoint and encoding (POST /api/v0/companies, form-encoded) and the response shape { meta, response }, which is valuable given there is no output schema. The destructiveHint=true annotation already signals a mutating operation, and 'MUTATES Accelo data' is consistent with it. Missing auth requirements and rate/idempotency behavior keeps this from 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.

Conciseness4/5

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

Front-loads the mutation warning, then endpoint, then return shape, then the update alternative — every clause carries information. The trailing parenthetical is dense and slightly awkward but not wasted text.

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?

For a 6-parameter mutation tool with no output schema, the description supplies the endpoint, encoding, response envelope, and the update/delete routing note, while the schema covers all parameters. It lacks auth/permission expectations and failure behavior, but nothing essential for correct invocation is missing.

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%, so every parameter (including the nested 'fields' bag) is already documented in the schema; the baseline is 3. The description adds the form-encoding detail and implies the typed fields are merged with 'fields' into the write body, but no per-parameter semantics beyond that.

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?

States a specific verb and resource — 'creates a new company (client organization)' — and marks it as a mutation up front. This clearly distinguishes it from sibling readers like get_company/list_companies and from other creators like create_contact or create_task.

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?

Gives useful routing context by noting there is no separate delete tool and that UPDATE is done by POSTing to /api/v0/companies/{id}. It does not mention the generic accelo_request sibling, which is the obvious fallback for non-create operations, so it stops short of full when/when-not guidance.

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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