Returns the current toolkit state: installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds value by enumerating the specific returned data (installed MCPs, connection status, accounts, catalog tool counts), which helps the agent understand the output scope beyond the basic read-only nature.
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, front-loaded sentence with no extraneous words. It clearly states the action and enumerates the return components, maintaining high information density without fluff.
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 read-only tool with no parameters and no output schema, the description fully covers the returned content (installed MCPs, connection status, accounts, tool counts). It is complete for the agent to know what to expect and how to use it.
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 tool has zero parameters, so the description does not need to explain them. The schema coverage is 100% (vacuous). The description adds the context of what state is returned, which is sufficient given no inputs.
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 tool returns the current toolkit state, specifying the exact components: installed MCPs, connection status, connected accounts, and catalog tool counts. This is a specific verb+resource and differentiates it from siblings like show_version or connect.
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 implies usage for inspecting toolkit state but does not explicitly state when to use it versus alternatives or provide exclusions. The purpose is clear, but there is no guidance on when not to use it or mention of related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool has a distinct name and purpose, with clear separation between read and write actions. However, the high number of similarly-prefixed tools (e.g., zapsign_documents_write_*) and the overlap between create and create_from_template could occasionally cause misselection.
Domain tools follow a consistent zapsign_<resource>_<action> pattern, with writes marked by _write_. However, platform-level tools (authenticate, connect, marketplace) break the pattern, and zapsign_list_accounts deviates from the resource-prefix convention.
35 tools is excessive, especially since many are flattened actions from a smaller set of underlying operations. The inclusion of non-domain platform tools further inflates the count, making the tool list feel heavy and harder to navigate.
The core ZapSign domain is well covered: documents, signers, templates, webhooks, checks, and account management all have CRUD-like operations. Minor gaps exist, such as no listing endpoint for checks and no webhook list (due to API limitations), but these are not fatal for typical workflows.