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Fred Search

fred_search
Read-onlyIdempotent

Search for economic data series by keyword. Returns series IDs, titles, and descriptions to identify the right indicator.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (1-1000, default 20)
_apiKeyYesFRED API key
order_byNoOrder results by: search_rank, series_id, title, units, frequency, seasonal_adjustment, realtime_start, realtime_end, last_updated, observation_start, observation_end, popularity, group_popularity. Default: search_rank
sort_orderNoSort direction: asc or desc. Default: asc for search_rank
search_textYesKeywords to search for (e.g., "mortgage rate", "housing starts")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoPresent when the result list was truncated.
seriesYesList of matching series
returnedNoHow many series are in `series` (capped by `limit`, default 20).
truncatedNoTrue when `returned` is less than `total_matches`.
total_matchesYesTotal number of matching series

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
      -  {
      -    "_apiKey": "your-fred-api-key",
      -    "limit": 10,
      -    "search_text": "mortgage rate"
      -  },
      -  {
      -    "_apiKey": "your-fred-api-key",
      -    "order_by": "popularity",
      -    "search_text": "unemployment",
      -    "sort_order": "desc"
      -  }
      -]New value: +[
      +  {
      +    "limit": 10,
      +    "search_text": "mortgage rate"
      +  },
      +  {
      +    "order_by": "popularity",
      +    "search_text": "unemployment",
      +    "sort_order": "desc"
      +  }
      +]
  2. Changed3 schema fields changed
    • addedOutput schema / properties / note
      Added value: +{
      +  "description": "Present when the result list was truncated.",
      +  "type": "string"
      +}
    • addedOutput schema / properties / returned
      Added value: +{
      +  "description": "How many series are in `series` (capped by `limit`, default 20).",
      +  "type": "number"
      +}
    • addedOutput schema / properties / truncated
      Added value: +{
      +  "description": "True when `returned` is less than `total_matches`.",
      +  "type": "boolean"
      +}
  3. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "series": {
      +      "description": "List of matching series",
      +      "items": {
      +        "properties": {
      +          "frequency": {
      +            "description": "Data frequency (d, w, m, q, a, etc.)",
      +            "type": "string"
      +          },
      +          "notes": {
      +            "description": "Additional notes about the series",
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "observation_end": {
      +            "description": "Latest available observation date",
      +            "type": "string"
      +          },
      +          "observation_start": {
      +            "description": "First available observation date",
      +            "type": "string"
      +          },
      +          "popularity": {
      +            "description": "Series popularity score",
      +            "type": "number"
      +          },
      +          "seasonal_adjustment": {
      +            "description": "Seasonal adjustment method",
      +            "type": "string"
      +          },
      +          "series_id": {
      +            "description": "FRED series ID",
      +            "type": "string"
      +          },
      +          "title": {
      +            "description": "Full title of the series",
      +            "type": "string"
      +          },
      +          "units": {
      +            "description": "Units of measurement",
      +            "type": "string"
      +          }
      +        },
      +        "required": [
      +          "series_id",
      +          "title",
      +          "units",
      +          "frequency",
      +          "seasonal_adjustment",
      +          "observation_start",
      +          "observation_end",
      +          "popularity",
      +          "notes"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "total_matches": {
      +      "description": "Total number of matching series",
      +      "type": "number"
      +    }
      +  },
      +  "required": [
      +    "total_matches",
      +    "series"
      +  ],
      +  "type": "object"
      +}
  4. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "_apiKey": "your-fred-api-key",
      +    "limit": 10,
      +    "search_text": "mortgage rate"
      +  },
      +  {
      +    "_apiKey": "your-fred-api-key",
      +    "order_by": "popularity",
      +    "search_text": "unemployment",
      +    "sort_order": "desc"
      +  }
      +]
  5. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already carry the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the description's burden is lower. It adds useful context by saying the response contains series IDs, titles, and descriptions, which indicates the tool returns search results rather than time-series data. It does not disclose details like default limits or how results are ordered, but the schema covers those.

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?

Two sentences with no filler. The first sentence states the action and resource; the second explains the return payload and the tool's purpose. Every sentence earns its place, and the most important information is front-loaded.

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

Completeness5/5

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

For a read-only keyword search tool with full schema coverage, an output schema, and annotations covering safety, the description is complete enough. It tells the agent what the tool searches, what it returns, and why it exists, so nothing critical is missing for correct selection and invocation.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents every parameter including search_text, limit, order_by, sort_order, and _apiKey. The description reinforces that search_text is the keyword input but adds no meaning beyond the schema. Baseline 3 is appropriate.

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

Purpose4/5

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

The description states a specific verb and resource: 'Search for economic data series by keyword.' It also clarifies the outcome (returns IDs, titles, descriptions) so an agent can see this is a discovery/identification tool rather than a data-retrieval tool. However, it does not explicitly contrast itself with sibling tools like fred_series_info or fred_get_series, so it stops short of full sibling differentiation.

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 phrase 'to identify the right indicator' implies the intended use case is choosing a series before fetching data, which gives reasonable context. But the description provides no explicit guidance about when to use fred_search versus alternatives such as fred_category, fred_series_info, or fred_get_series, and it does not state exclusions.

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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