FMP MCP Server

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

Annotations already provide readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true, covering safety and idempotency. The description adds valuable context about the scope ('today's market snapshot') and return content ('sector rankings, top 5 gainers/losers, most actively traded names'), enhancing behavioral understanding without contradicting annotations.

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 front-loaded with the core purpose in the first sentence and details the return values in the second. Both sentences earn their place by providing essential information without redundancy, making it highly efficient and well-structured.

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 the tool's low complexity (0 parameters), rich annotations covering key behavioral traits, and the presence of an output schema (which handles return value documentation), the description is complete. It effectively communicates what the tool does and what it returns, leaving no significant gaps for an AI agent.

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?

With 0 parameters and 100% schema description coverage, the baseline is 4. The description appropriately does not discuss parameters, as none exist, and focuses on the tool's function and output, which is sufficient given the empty input 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's purpose with specific verbs ('Get today's market snapshot') and resources ('sector performance, biggest movers, and most active stocks'), distinguishing it from siblings like 'market_context' or 'price_history' by focusing on a comprehensive daily overview rather than specific aspects.

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 implies usage context ('today's market snapshot') for obtaining a broad market overview, but does not explicitly state when to use this tool versus alternatives like 'market_context' or 'stock_search'. It provides clear context but lacks explicit exclusions or named alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.