anvil_current_userGet the authenticated Anvil user (from the API key) and the organizations they belong to (eid, name, slug). Good first call to discover org slugs/eids for other tools. GraphQL query: currentUser.
| 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, and the description adds the list of returned fields and the GraphQL query name. This provides additional context beyond the annotations, such as the purpose for discovering org identifiers.
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 three sentences, front-loaded with the main action, and includes a usage hint and technical note (GraphQL query). Every sentence adds value with no wasted words.
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 zero parameters and a simple read operation, the description fully explains what is returned (user and organizations with specific fields) and its purpose. The sibling tools are clearly different, and no output schema is needed as the description details the return shape.
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?
There are no parameters, and schema description coverage is 100% (trivially). The description does not need to add parameter semantics; it implicitly confirms no parameters are required. Baseline score of 4 applies.
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 gets the authenticated user and their organizations with specific fields (eid, name, slug). It distinguishes from sibling tools by noting it's a good first call for discovering org slugs/eids.
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 explicitly says 'Good first call to discover org slugs/eids for other tools,' providing clear usage context. It implies it's a read-only, no-parameter call but does not explicitly mention when not to use it or alternatives.
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 function: user info, PDF creation/filling, e-signature management, and workflow queries. No two tools have overlapping purposes; even the two PDF tools (fill_pdf vs generate_pdf) are clearly separated by input type.
All tools use the 'anvil_' prefix followed by verb_noun in snake_case (e.g., create_etch_packet, get_cast). The pattern is perfectly consistent across all 10 tools.
10 tools cover the major Anvil capabilities (PDF, e-sign, organization, workflows) without unnecessary redundancy. The count is well-scoped for the server's purpose.
The set lacks list/update/delete operations for several resources (e.g., no list_casts, no update_etch_packet). While key create and get operations are present, agents may need to work around missing CRUD coverage.