Return summary stats of how this MCP server has been used (top tools called, success rate, recent activity). Free. Use to verify your own integration is hitting the right tools.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It mentions the tool is free and returns stats, but does not state whether it has side effects, requires authentication, or has rate limits. For a stat retrieval tool, more clarity on read-only nature and output details would be beneficial.
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 concise with two short sentences, each serving a clear purpose: first defines the function, second provides usage context. There is no unnecessary verbiage.
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 no parameters, no output schema, and no annotations, the description covers the essential aspects: what the tool returns and a typical usage scenario. It could be slightly more detailed about response structure or limitations, but overall it is sufficient.
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 input schema has no parameters, so schema description coverage is 100%. The description adds value by detailing what the output contains (top tools, success rate, recent activity), which helps the agent understand the semantic meaning beyond the empty schema.
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 summary stats about MCP server usage, including specific items like top tools called, success rate, and recent activity. It effectively conveys the core function, though it does not explicitly contrast with sibling tools to further distinguish itself.
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 provides a practical use case ('verify your own integration is hitting the right tools') and notes it's free. However, it lacks explicit guidance on when not to use this tool or mention of alternatives among siblings, leaving room for ambiguity.
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.
Most tools occupy distinct roles (install, usage stats, wallet setup), but list_endpoints and pricing_info overlap substantially: both report paid endpoints and prices, even though one emphasizes live status and the other detailed fees/payment networks. Descriptions help separate them, but an agent could still pick the wrong one for a pricing question.
Names are uniformly snake_case and readable, but the pattern is mixed: install_snippets and list_endpoints use verb_noun, while pricing_info, usage_stats, and wallet_helper use noun-based names. This is a readable mixed convention rather than a chaotic one.
Five tools is a reasonable number for a small server, but for a product called 'Prediction Market Data for AI Agents' the set is oddly scoped: everything is onboarding/pricing/usage meta-tools rather than data tools. The count is not excessive, but it feels thin for the apparent market-data purpose.
The server promises prediction market data, yet none of the five tools retrieves markets, odds, prices, positions, or any actual market data. Even if the free helper tools are complete, the core data surface is entirely absent, leaving agents with no way to fulfill the server's stated purpose.