credential_deleteRemove a saved credential. If label is provided, removes only that specific entry. If no label, removes ALL entries for that credential name.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Credential name to delete (e.g. "ios_app_id"). | |
| label | No | Label of the specific entry to delete. Omit to remove all entries for this credential name. | |
| context | No | "personal" or "team:<id>". Defaults to personal. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already include destructiveHint=true, and the description adds the key destructive nuance that omitting label removes ALL entries for the credential name. This goes beyond the schema and meaningfully warns about the destructive scope. No contradiction with 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?
Two sentences with no filler. The core action is front-loaded, and the conditional destructive behavior is stated immediately after. Every sentence 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 destructive deletion tool with a full parameter schema and no output schema, the description covers the essential behavioral decision: label vs no label. It does not address edge cases like nonexistent credentials or confirmation behavior, but the annotations and schema cover most remaining context needed to invoke it correctly.
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 description coverage is 100%, so the schema already explains all parameters. The description reinforces the label semantics (specific entry vs all entries) but adds little new meaning beyond the parameter descriptions already present.
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 states a specific verb ('Remove') and resource ('saved credential'), and clearly explains the two deletion modes: specific label vs all entries. This distinguishes it from sibling credential_* tools and leaves no ambiguity about what the tool does.
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 condition for using the label parameter is described, giving some usage guidance. However, there is no explicit comparison to alternatives like credential_save or credential_list, so tool-selection guidance is only implied by the delete verb and title.
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.
Tools are grouped by clear resource prefixes (account_, brain_, connector_, credential_, file_, job_, key_), and most actions have distinct purposes. A few boundaries overlap—brain_admin's lint action duplicates brain_lint, and account_preferences/setup/switch could momentarily confuse—but the descriptions resolve most ambiguity.
The dominant pattern is resource_verb for actions (file_read, job_cancel, key_create) and resource_noun for state views (credits_balance, brain_settings, account_preferences), which is readable. However, exceptions like discover, use_tool, top_up_credits, and feedback_request_tool break the pattern, and the set is not consistently verb_noun.
47 tools is well beyond the comfortable range; even though prefixes organize them, the agent faces a large selection surface with many narrowly scoped tools. A more consolidated set with action-based subcommands would be easier to navigate.
Core workflows are covered end-to-end: account setup and billing, connector and credential management, file CRUD, job polling, key lifecycle, brain knowledge management, and catalogue discovery/execution. Gaps are minor—outfit/persona/product/scene are list-only, connectors lack an update operation, and there is no explicit single-page brain get—but agents can generally work around them.