List formats and capabilities
mcpFormatsWhat AILANG Parse can read and write, how to send it a document, and the sample documents you can try without one. No sign-in needed.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
mcpFormatsWhat AILANG Parse can read and write, how to send it a document, and the sample documents you can try without one. No sign-in needed.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Input schema / properties / _Removed value: -{
- "type": "string"
-}Input schema / requiredPrevious value: -[
- "_"
-]New value: +[]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnly/non-destructive/openWorld=false, so the bar is lower. The description adds auth context not present in annotations ('No sign-in needed') and previews the response content (formats, submission method, sample documents), which is useful behavioral disclosure beyond the structured fields.
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?
A single, front-loaded sentence that wastes no words and leads with the core offering. It packs three items slightly densely but remains readable.
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?
With zero params, no output schema, and annotations covering the safety profile, the description adequately conveys purpose, auth requirement, and rough return content for a simple read-only discovery tool. Minor gap: no explicit routing to operational siblings.
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?
Zero parameters, so per the rubric the baseline is 4. There is no parameter surface for the description to clarify or omit.
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 purpose: it enumerates what AILANG Parse can read/write, how to submit a document, and available samples. It's clearly the discovery/capabilities endpoint, distinguishable in intent from operational siblings like mcpParse or mcpConvert, though it doesn't name any sibling explicitly.
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?
Usage is implied (consult this to learn formats and try samples) but there is no explicit 'when to use this vs X' guidance or mention of alternatives such as mcpParse. The 'no sign-in needed' clause hints at a pre-auth discovery context without stating it.
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.