India's official statistics from the Ministry of Statistics and Programme Implementation, queryable via natural language.
Fetches statistical data from a MoSPI dataset. This is the final step of the workflow. It requires filter values from get_metadata — filter codes are arbitrary (e.g., indicator_code=3 means "Unemployment Rate" in PLFS but something different in other datasets). All filter parameters including limit and page go inside the filters dict, not as top-level arguments. Step 4 of: list_datasets → get_indicators → get_metadata → get_data
Returns the full list of available indicators for a given dataset. Datasets often have broader coverage than expected — for example, ASI covers 57 indicators (capital structure, wages, employment, GVA, fuel consumption), and GENDER covers 147 indicators across health, education, labor, and crime. For PLFS and ASUSE, indicators are grouped by frequency_code: - PLFS frequency_code=1 (Annual): all 8 indicators including wages - PLFS frequency_code=2 (Quarterly): indicators 1-3 only - PLFS frequency_code=3 (Monthly): indicators 1-3 only frequency_code selects the indicator set, not time granularity. Step 2 of: list_datasets → get_indicators → get_metadata → get_data
Returns the valid filter values (states, years, quarters, etc.) for a given dataset and indicator. Filter codes are arbitrary and dataset-specific — for example, PLFS state_code 99 means "All India", and NAS frequency_code 1 means "Annual". These values cannot be inferred or guessed from parameter names alone. The returned filter_values and api_params should be used as-is when calling get_data. Step 3 of: list_datasets → get_indicators → get_metadata → get_data
Returns an overview of all MoSPI statistical datasets with descriptions and coverage. This is the starting point ΓÇö call this first to identify the right dataset. The API covers 500+ indicators across employment, prices, industry, national accounts, health, education, disability, housing, environment, trade, and more. Each dataset has its own indicator codes, filter parameters, and valid values ΓÇö these are not standardized and cannot be inferred or guessed from parameter names alone. Four-step workflow (each step depends on the previous): 1. list_datasets() ΓÇö identify the dataset 2. get_indicators(dataset) ΓÇö list available indicators 3. get_metadata(dataset, indicator_code) ΓÇö retrieve valid filter values 4. get_data(dataset, filters) ΓÇö fetch the data Returns: dict with 'datasets' (name, description, use_for for each dataset) and 'workflow' (the four-step sequence).
The MoSPI MCP integration connects your Dench AI CRM directly to MoSPI MCP, so agents can read and act on your MoSPI MCP data as part of everyday work — answering questions in chat, keeping your CRM in sync, and running automations without anyone copying data between tools.
4 actions are available for agents to invoke on your behalf. Every call runs through MoSPI MCP's own authorization, scoped to the account you connect.
Sign in to your Dench workspace and open Integrations.
Find MoSPI MCP and click Connect — you'll authorize access through MoSPI MCP's own sign-in flow. No API keys or code required.
Ask an agent to use MoSPI MCP in chat, or call it from an automation.
Manage or disconnect the connection any time from workspace settings.
The Dench MoSPI MCP integration connects your AI CRM to MoSPI MCP, so AI agents can work with your MoSPI MCP data as part of chats, automations, and CRM workflows. You connect your account once, and every agent in your workspace can use it — governed by your workspace permissions.
The MoSPI MCP integration currently exposes 4 actions, including Get data, Get indicators, Get metadata, and List datasets. Agents invoke them on your behalf from chat or from automations.
No. You connect MoSPI MCP from your Dench workspace using MoSPI MCP's own sign-in and authorization flow — no API keys to copy, no glue code to maintain.
Connections are authorized through MoSPI MCP's own authentication flow, and Dench stores only the authorization needed to act on your behalf. You can review and disconnect the MoSPI MCP connection from your workspace settings at any time.