Federal Reserve Economic Data (FRED) MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the action (search), return format (matching series with IDs, titles, metadata), and context (when you know what you're looking for). However, it doesn't mention potential limitations like rate limits, authentication needs, error handling, or pagination behavior (implied by offset/limit parameters but not explained). For a search tool with 10 parameters and no annotations, this is adequate but leaves gaps in behavioral context.

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 appropriately sized and front-loaded: it starts with the core purpose, then specifies the return format, and ends with usage guidance. Both sentences are essential—the first defines the tool, and the second provides context. There is zero waste, making it highly efficient and easy to parse.

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 complexity (10 parameters, no annotations, no output schema), the description is moderately complete. It covers the purpose, return format, and usage context adequately. However, it lacks details on behavioral aspects like error handling or rate limits, and without an output schema, it doesn't fully explain return values beyond high-level metadata. For a search tool with many parameters, this is a minimal viable description but has clear gaps in completeness.

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 schema description coverage is 100%, meaning all parameters are documented in the input schema. The description adds minimal value beyond the schema: it mentions 'keywords, tags, or filters' which loosely maps to parameters like search_text, tag_names, and filter_variable, but doesn't provide additional syntax or usage details. With high schema coverage, the baseline is 3, and the description doesn't significantly enhance parameter understanding.

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: 'Search for FRED economic data series by keywords, tags, or filters. Returns matching series with their IDs, titles, and metadata.' It specifies the verb ('Search'), resource ('FRED economic data series'), and scope (search methods and return format). It also distinguishes from sibling tools by stating 'Use this to find specific series when you know what you're looking for,' implying fred_browse might be for exploration and fred_get_series for retrieving known series.

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 clear context for when to use this tool: 'Use this to find specific series when you know what you're looking for.' This gives a general guideline, but it doesn't explicitly state when not to use it or name specific alternatives among the siblings (e.g., fred_browse for browsing vs. searching). The guidance is helpful 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.