This connector has been replaced by https://glama.ai/mcp/connectors/io.favcrm/favcrm/admin
Get full order detail including line items.
| Name | Required | Description | Default |
|---|---|---|---|
| orderId | Yes | The order UUID |
| Name | Required | Description | Default |
|---|---|---|---|
| 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 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, establishing a safe read operation. The description adds value by specifying what details are returned ('including line items'), which goes beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence (6 words) that effectively communicates the purpose without any redundant information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with an output schema (not shown but indicated), the description is sufficient. The sibling tools provide clear context (e.g., list_orders for listing all orders, update_order_status for modifications).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for the single parameter ('The order UUID'). The tool description does not add additional meaning beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get full order detail including line items' uses a specific verb ('Get') and resource ('order detail') and further specifies scope ('including line items'), distinguishing it from sibling tools like list_orders which only list summaries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies usage for retrieving a single order's full details. The context signals and sibling names (e.g., list_orders, update_order_status) provide differentiation, though no explicit when-not-to-use guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.