FavCRM

This connector has been deprecated

This connector has been replaced by https://glama.ai/mcp/connectors/io.favcrm/favcrm/admin

attach_post_cover_from_job

Attach a previously generated ai-media job's output as the post's featuredImage. Use when generate_post_cover timed out (job kept running) or when reusing the same generation across multiple posts. Verifies the job belongs to your company and succeeded. Does NOT charge credits — credits were charged at submit time.

Input Schema

TableJSON Schema

Name	Required	Description
`jobId`	Yes	The ai-media job ID (from generate_image, generate_post_cover, or POST /v6/merchant/ai-media/generate)
`postId`	Yes	The post ID
`assetIndex`	No	Which asset to use when the job produced multiple outputs. Default 0.
`pollIfRunning`	No	When true, advance polling once if the job is still running. Default true.
`pollTimeoutMs`	No	When pollIfRunning is true, wait up to this long for terminal state. Default 30000.

Output Schema

TableJSON Schema

Name	Required	Description
`data`	Yes	Tool result payload — shape varies per tool, see the tool description
`summary`	Yes	One-line human-readable summary of the action
`renderType`	Yes	UI rendering hint for the result

TDQS

A4.8/5.0

Behavior4/5

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

The description discloses that it verifies the job belongs to the company and succeeded, and does not charge credits (charged at submit). This adds behavioral context beyond annotations. However, it doesn't mention potential side effects like overwriting an existing cover, though annotations already show destructiveHint=false.

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 description is very concise: three sentences that front-load the purpose, then usage context, then verification and credit info. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the full schema coverage, output schema exists, and annotations provide some safety hints, the description is complete. It covers purpose, usage scenarios, verification, and credit behavior, making it sufficient for an agent to decide when and how to invoke.

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

Parameters5/5

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

Schema coverage is 100%, so baseline is 3. The description adds meaning by explaining the overall scenario (reusing a job), which helps interpret parameters like jobId, pollIfRunning, etc. It provides enough context to understand parameter roles beyond the schema descriptions.

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 attaches a previously generated ai-media job's output as the post's featuredImage. It specifies the verb 'attach' and resource 'post cover', and distinguishes from siblings like generate_post_cover and upload_post_cover_from_url by indicating reuse scenario.

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

Usage Guidelines5/5

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

Explicitly says when to use: when generate_post_cover timed out (job kept running) or when reusing the same generation across multiple posts. It provides clear context for when this tool is appropriate versus alternatives.

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

All FavCRM tools Inspect

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TDQS

A3.6/5.0

Disambiguation5/5

Each tool targets a distinct resource and action, with clear descriptions that minimize ambiguity. Even related tools like create_post vs create_post_type are well-separated by their targets.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern (e.g., create_account, list_services, update_post), with no mixing of naming conventions. The pattern is predictable throughout the set.

Tool Count1/5

190 tools is excessively large for any server, far exceeding the typical 3-15 tool range. The sheer volume overwhelms agents and suggests poor scoping, even for a comprehensive CRM platform.

Completeness4/5

The tool set covers CRUD operations across many domains (CRM, bookings, marketing, CMS, etc.), but notable gaps exist (e.g., no delete_account, delete_contact, update_booking). These are minor given the vast surface.

Resources

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