This connector has been replaced by https://glama.ai/mcp/connectors/io.favcrm/favcrm/admin
List booking resources (rooms, equipment, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 20) |
| 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 indicate read-only, non-destructive, and idempotent behavior. The description does not add additional behavioral context such as pagination details, rate limits, or data freshness. Given annotation coverage, a score of 3 is appropriate.
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 that front-loads the core purpose. It could include slightly more detail without becoming verbose, but it is appropriately sized.
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?
Given the tool's low complexity, simple parameters, and the presence of an output schema, the description is fairly complete. However, it omits any mention of scoping (e.g., which resources are listed) or default behavior.
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 descriptions for the single parameter 'limit'. The tool description does not add any further meaning beyond what the schema provides, so baseline 3 is correct.
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 clearly states the verb 'List' and the resource 'booking resources' with examples (rooms, equipment), making the purpose unmistakable. It distinguishes from sibling list tools by specifying the resource type.
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 provides no guidance on when to use this tool vs alternatives, no when-not-to-use information, and no context about prerequisites or typical scenarios.
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.