Skip to main content
Glama

Nass

by io.github.pipeworx-io
OverviewDiscussionsAdmin

Nass Prices

nass_prices
Read-onlyIdempotent

Get prices received by US farmers for crops and livestock by commodity, state, and year. Track agricultural commodity price trends and market movements.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoYear or range (optional)
stateNoState name (optional, defaults to national)
_apiKeyYesNASS API key
commodityYesCommodity: "CORN", "SOYBEANS", "WHEAT", "CATTLE", "HOGS", "MILK", "CHICKENS"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesPrices received by farmers
countYesNumber of records returned
truncatedYesTrue if results exceed 200 records

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "count": {
+      "description": "Number of records returned",
+      "type": "integer"
+    },
+    "data": {
+      "description": "Prices received by farmers",
+      "items": {
+        "properties": {
+          "agg_level": {
+            "description": "Aggregation level",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "commodity": {
+            "description": "Commodity name",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "county": {
+            "description": "County name",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "description": {
+            "description": "Price statistic description",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "frequency": {
+            "description": "Frequency",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "period": {
+            "description": "Reference period",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "stat_category": {
+            "description": "Always PRICE RECEIVED",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "state": {
+            "description": "State name",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "unit": {
+            "description": "Price unit (e.g., $/BU, $/CWT)",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "value": {
+            "description": "Price received by farmers",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "year": {
+            "description": "Year",
+            "type": [
+              "integer",
+              "null"
+            ]
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "truncated": {
+      "description": "True if results exceed 200 records",
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "count",
+    "data",
+    "truncated"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-nass-api-key",
+    "commodity": "CORN",
+    "state": "ILLINOIS",
+    "year": "2024"
+  },
+  {
+    "_apiKey": "your-nass-api-key",
+    "commodity": "CATTLE",
+    "year": "2020:2025"
+  }
+]
  3. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds that the tool provides prices received by US farmers, which is useful context but does not disclose additional behavioral traits like data update frequency, aggregation, or pagination. The description does not contradict annotations.

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 concise sentences front-load the key purpose and scope. No redundant or filler content. Every word earns its place.

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 presence of an output schema (true), the description does not need to explain return values. It adequately covers the filtering dimensions and intent. However, it omits mention of the required API key, but that is already captured in the input schema. The description is mostly complete for a read-only data retrieval tool with good annotations.

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%, with each parameter having a description. The description restates that it filters by commodity, state, and year but adds no new semantic detail beyond the schema. The baseline of 3 is appropriate as the description neither adds nor detracts.

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 it retrieves prices received by US farmers for crops and livestock, specifying dimensions (commodity, state, year). The verb 'Get' and resource 'prices' are explicit, and the tool is distinct from sibling tools like nass_crop_production or nass_query which cover other data types.

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 use for tracking agricultural price trends but does not explicitly state when to prefer this over siblings (e.g., nass_crop_production for production data, nass_livestock for livestock-specific data). No exclusions or alternative guidance provided.

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

All Nass toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources