Fetch the raw stored content of a document. Defaults to your own handle and the latest version.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Document name. | |
| handle | No | Owner handle. Defaults to the authenticated user. | |
| version | No | Version number. Defaults to the latest. |
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| appUrl | Yes | ||
| handle | Yes | ||
| rawUrl | Yes | ||
| deleted | No | ||
| snippet | No | ||
| version | Yes | ||
| language | No | ||
| visibility | No | ||
| contentType | No |
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, so the read-only nature is covered. The description adds useful behavioral context by stating that the content is 'raw stored content' and that handle/version default to your own and latest respectively, which helps the agent predict the tool's behavior.
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 two short sentences with no filler. The core action is front-loaded, followed by the most important default behaviors, making it easy to scan and understand.
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?
The tool is simple, has full parameter documentation, a read-only annotation, and an output schema. The description, plus the structured data, gives an agent everything 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 all three parameters (name, handle, version) are already documented in the schema. The description only restates the default behavior for handle and version, adding no extra meaning beyond the structured parameter descriptions.
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 uses a specific verb ('Fetch') and a clear resource ('raw stored content of a document'), which precisely identifies the operation. This distinguishes it from siblings like create_doc and search_docs without ambiguity.
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 makes the basic usage clear: fetch a document's raw content, defaulting to your own handle and the latest version. However, it does not explicitly mention when to prefer this over search_docs or create_doc, leaving that comparison implied rather than stated.
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 operation: create, retrieve, and search. There is no overlap between the actions, and the descriptions reinforce their differing purposes.
All tool names follow a consistent verb_noun pattern: create_doc, get_doc, search_docs. The only slight variation is singular 'doc' versus plural 'docs', which does not harm predictability.
Three tools is a reasonable, focused set for a document storage service. Each tool handles a distinct core need and none feel redundant or unnecessary.
The core document lifecycle of create, read, and search is covered, with versioning handled through create. A minor gap is the absence of a delete or full list-all operation, though agents can likely work around that for most workflows.