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OpenWeb-Ninja

OpenWeb Ninja MCP

Official

gemini

Send a chat prompt to Google's AI and receive the response. Get AI-powered answers via the MCP server.

Instructions

Relay a chat prompt to Google Gemini and get the model's response.

Operations (set "operation" to one of these; put its parameters in "args"):

  • chat (required: message): Chat

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsNoParameters for the chosen operation as key/value pairs (see the tool description for required params).
operationYesWhich endpoint to call. See the tool description for each operation and its parameters.
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description carries the full burden of behavioral disclosure. It states the core behavior (relay and get a response) and lists the operation with its required message parameter, but it does not mention rate limits, potential errors, or any other caveats. For a simple chat relay, this is adequate but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately brief: two sentences and a one-item bullet list. It front-loads the main purpose and then explains operations and parameters without any filler or redundant content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one operation, one required parameter), the description is reasonably complete. It clearly identifies the operation and parameter, but it does not describe the response format or any edge cases. Since there is no output schema, a little more detail about the return value could have improved completeness, but the tool's straightforward nature makes this acceptable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema's 'args' field is generic and defers to the description for parameter details. The description compensates by explicitly stating that 'chat' requires a 'message' parameter and that parameters go in 'args', providing the necessary semantic meaning beyond the schema's sparse structure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: relaying a chat prompt to Google Gemini and returning the model's response. The verb 'relay' and specific resource 'Google Gemini' make the purpose explicit and distinguish it from sibling chat tools like ChatGPT and Copilot.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool (when you need to interact with Google Gemini) but does not explicitly compare it to alternatives or state when not to use it. There is no mention of exclusions or alternative tool recommendations, leaving the context to be inferred from the tool name and sibling set.

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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