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Glama

Data Gov In

by io.github.pipeworx-io

Resource Data

resource_data
Read-onlyIdempotent

Fetch records from any India Open Government Data (data.gov.in) resource by its resourceId. Supports pagination, per-field filtering, field projection, and sorting. The resourceId is the UUID shown on a dataset's page on data.gov.in (and in its API URL, e.g. api.data.gov.in/resource/). Example resourceId 9ef84268-d588-465a-a308-a864a43d0070 is "Current Daily Price of Various Commodities from Various Markets (Mandi)" with fields like state, district, market, commodity, variety, grade, arrival_date, min_price, max_price, modal_price. Use resource_meta first if you do not know a resource's field ids.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoOptional sort spec mapped to sort[field]=direction, where direction is "asc" or "desc", e.g. {"modal_price":"desc"}.
limitNoMax records to return (default 10). The API caps page size; use offset to page.
fieldsNoOptional comma-separated list of field ids to return (projection), e.g. "state,commodity,modal_price".
offsetNoRecords to skip for pagination (default 0).
_apiKeyYesdata.gov.in API key
filtersNoPer-field exact-match filters, mapped to filters[field]=value query params. Field ids come from the resource schema (see resource_meta), e.g. {"state":"Punjab","commodity":"Apple"}.
resourceIdYesThe dataset resource UUID from its data.gov.in page (e.g. "9ef84268-d588-465a-a308-a864a43d0070").

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-data-gov-in-api-key",
+    "limit": 10,
+    "offset": 0,
+    "resourceId": "9ef84268-d588-465a-a308-a864a43d0070"
+  },
+  {
+    "_apiKey": "your-data-gov-in-api-key",
+    "fields": "state,commodity,modal_price,arrival_date",
+    "filters": {
+      "commodity": "Apple",
+      "state": "Punjab"
+    },
+    "limit": 20,
+    "offset": 0,
+    "resourceId": "9ef84268-d588-465a-a308-a864a43d0070",
+    "sort": {
+      "modal_price": "desc"
+    }
+  }
+]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: pagination, per-field filtering, field projection, sorting, and the exact format/location of resourceId. It stops short of covering error handling or response format, but the annotation coverage lowers the burden.

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?

Five sentences, all front-loaded with the core action. No filler; the example resource and field list earn their place. The structure moves from general capability to specific resourceId guidance to an actionable pointer to resource_meta.

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 7 parameters, nested objects, and no output schema, the description covers purpose, capabilities, example usage, and relationship to a sibling tool. It does not explicitly describe the return format, but the read-only annotations and 'fetch records' phrasing make the intent clear. Overall, highly complete for a data-fetching tool.

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

Parameters4/5

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

Schema description coverage is 100% for all 7 parameters, so baseline is 3. The description goes beyond by providing a concrete example resourceId and listing its fields (state, district, market, commodity, etc.), which helps the agent understand possible filter/sort values. It also directs to resource_meta for field discovery.

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 opens with a specific verb and resource: 'Fetch records from any India Open Government Data (data.gov.in) resource by its resourceId.' It clearly distinguishes this tool from siblings like resource_meta by focusing on record retrieval, not metadata.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly instructs when to use an alternative: 'Use resource_meta first if you do not know a resource's field ids.' This gives a clear precondition and names the sibling tool, providing both when-to-use and when-to-defer guidance.

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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TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer natural-language data questions. The six Polymarket/prediction-market tools also blur together, and ai_visibility_check versus scan_competitor_ai_presence are near-duplicates.

Naming Consistency4/5

Snake_case is used consistently, and most tools follow a verb-first or domain-prefixed pattern (ask_pipeworx, compare_entities, subscribe, polymarket_*). Minor deviations like entity_profile, resource_data, and ai_visibility_check are noun-first, but nothing is chaotic or mixed-cased.

Tool Count2/5

33 tools is excessive for a server named 'Data Gov In' whose actual domain-specific surface is only resource_data and resource_meta. The rest are generic Pipeworx, prediction-market, memory, and utility tools that do not belong to the apparent India open-data scope.

Completeness1/5

For a data.gov.in server, the surface is severely incomplete: there is no way to search or list datasets/resources, only fetch metadata and data for a known resourceId. The overwhelming majority of tools serve unrelated domains, so an agent using this server for Indian government data will hit dead ends immediately.

Resources