create_api_key
Generate API keys to authenticate and access AnythingLLM workspace features programmatically.
Instructions
Create a new API key
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Name for the API key |
Generate API keys to authenticate and access AnythingLLM workspace features programmatically.
Create a new API key
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Name for the API key |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Create a new API key' implies a write operation that likely requires specific permissions and may have side effects (e.g., generating a secret key), but the description doesn't mention authentication needs, rate limits, whether the key is immediately usable, or what happens on failure. This is inadequate for a mutation tool with zero annotation coverage.
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, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable and easy to parse. Every word earns its place by conveying essential purpose.
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 that this is a mutation tool with no annotations, no output schema, and minimal parameter guidance, the description is incomplete. It doesn't address key contextual aspects like what the tool returns (e.g., the generated key value), error conditions, or system-specific details. For a tool that creates security credentials, this lack of information is significant.
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?
The input schema has 100% description coverage, with the single parameter 'name' documented as 'Name for the API key'. The description adds no additional semantic context beyond what the schema provides, such as naming conventions or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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 'Create a new API key' clearly states the action (create) and resource (API key), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_api_keys' or 'delete_api_key' beyond the obvious verb difference, missing an opportunity to specify what kind of API key or for what system.
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 versus alternatives. It doesn't mention prerequisites (e.g., authentication level), when not to use it (e.g., if you need to list existing keys first), or how it relates to siblings like 'list_api_keys' or 'delete_api_key'. This leaves the agent without context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/raqueljezweb/anythingllm-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server