Manufact

MoSPI Data Server

mcp.mospi.gov.in

Access India's official government statistics through natural language. MoSPI's MCP server connects AI assistants to national datasets covering GDP, inflation, employment, industrial production, higher education, health, energy, environment, trade, and more. All data comes directly from the Ministry of Statistics and Programme Implementation (MoSPI), Government of India, via the eSankhyiki portal.

Protocol: MCP 2025-11-25
Server version: 2.3.0
Supports: Tools
Resources
Prompts
Logging

Overall score

Last reviewed at Oct 6, 2026, 13:23:44 UTC

Server metadata

3 of 8 fields30/1002.4 / 8 pts

Identity, discovery, and usage metadata advertised during the MCP handshake.

Stable server name

MoSPI Data Server

10/10Source

Human-readable title

Add a human-readable title for clients and directories.

0/10Source

Useful description

Describe what the server helps an agent do.

0/20Source

Server version

Version 2.3.0

10/10Source

Public website

Link to a public website or documentation page.

0/10Source

Scalable or high-resolution icon

Advertise a vector or at least 128px server icon.

0/10Source

Server instructions

Add concise instructions that explain how an agent should use the server.

0/20Source

Declared capabilities

Supports Tools, Resources, Prompts, Logging.

10/10Source

Extensions

io.modelcontextprotocol/ui

Protocol

Pass100/10016 / 16 pts

Connection, authentication, and protocol compatibility.

MCP negotiation succeeds (v1/v2)

MCP legacy negotiation succeeded in 4617ms

Source

Resources list responds

0 resource(s) returned

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Tools list returns results

4 tool(s) returned

Source

Server declares tools capability

Server declares tools capability in initialize response

Source

Tools

Pass100/10024 / 24 pts

Tool definitions, annotations, and client compatibility.

Skills over MCP resources are readable

Server does not advertise the Skills over MCP extension

All tools have descriptions

All tools have non-empty descriptions

All tools have OpenAI behavior hints

All tools declare the three OpenAI behavior hints as booleans

Source

Claude Code metadata fits its 2 KB fields

Tool descriptions and server instructions fit Claude Code's 2 KB fields

Source

Claude tool names are within 64 characters

All tool names are within Claude's 64-character limit

Source

Claude tools declare applicable behavior hints

All tools include an applicable readOnlyHint or destructiveHint

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Cursor tool-name budget advisory

No tool name independently exhausts Cursor's observed 60-character combined budget

Observed behavior

Tool names use valid characters

All tool names use valid characters

Source

Tool names follow the MCP 1–128 character range

All tool names follow the MCP recommended length

Source

ChatGPT tool names are unique

All tool names are unique

Source

All tools have a display title

Source

Tool names follow MCP uniqueness guidance

All tool names are unique

Source

Declared output schemas have a valid basic structure

4 declared output schema(s) pass basic structural validation; schemas may describe any JSON value, including arrays

Source

OpenAI file parameters use valid schemas

All declared OpenAI file parameters use reviewer-valid schemas

Source

Tool input header annotations are valid

All x-mcp-header annotations satisfy Streamable HTTP requirements

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Tool input schemas have a valid object structure

All tool input schemas have a valid object structure

Source

Tool text has no hidden control characters

No invisible or control characters found in tool-facing text

Source

MCP Apps

Skipped-0 / 20 pts

App resources, metadata, and rendering requirements.

Tool visibility metadata is valid

No view resources found — view checks skipped

Source

CSP metadata covers literal external origins

No view resources found — view checks skipped

Source

Tool invocation metadata present

No view resources found — view checks skipped

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View resource envelope is valid

No view resources found — view checks skipped

View resources declare a domain

No view resources found — view checks skipped

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Declared domains respond

No view resources found — view checks skipped

View resource metadata complete

No view resources found — view checks skipped

Source

Tool-linked resource URI is readable

No view resources found — view checks skipped

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All discovered view resources were inspected

No view resources found — view checks skipped

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Tool documentation quality

4 tools reviewed76/10024.3 / 32 pts

How clearly each tool’s title, description, input and output schemas, and behavior annotations guide an agent.

get_indicatorsTitles 99Descriptions 80Inputs 19Annotations 75Outputs 461/100

Title99/100

Browse Dataset Indicators

The title clearly communicates the tool’s action and subject. Keep it concise.

Description80/100

Returns the full list of available indicators for a given dataset. Datasets often have broader coverage than expected ΓÇö 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 ΓåÆ get_indicators ΓåÆ get_metadata ΓåÆ get_data

Describe the returned information so the agent knows whether it will answer the request.

Inputs19/100

2 of 9 inputs have descriptions. Add descriptions to the missing inputs, including where to obtain IDs and how to supply values.

dataset

Dataset name ΓÇö one of: PLFS, CPI, IIP, ISP, ASI, NAS, WPI, ENERGY, AISHE, ASUSE, GENDER, NFHS, ENVSTATS, RBI, NSS77, NSS78, NSS76, NSS75E, NSS79, CPIALRL, HCES, TUS, EC, UDISE, MNRE, NSS80, NSS73. For CPI, IIP, ISP, WPI: returns available base years and frequencies.

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

user_query

The user's original question. Captured for telemetry analytics; not echoed back in the response.

Clear enough to supply this argument.

classification_year

Not provided

Missing description. Explain what this value means and how to supply it.

base_year

Not provided

Missing description. Explain what this value means and how to supply it.

frequency

Not provided

Missing description. Explain what this value means and how to supply it.

frequency_code

Not provided

Missing description. Explain what this value means and how to supply it.

level

Not provided

Missing description. Explain what this value means and how to supply it.

series

Not provided

Missing description. Explain what this value means and how to supply it.

Format

Not provided

Missing description. Explain what this value means and how to supply it.

Annotations75/100

Declare idempotentHint based on the tool’s actual behavior.

{
  "readOnlyHint": true,
  "openWorldHint": true,
  "destructiveHint": false
}

Output schema4/100

Declare the result fields and their types in the output schema.

View output schema

{
  "type": "object",
  "additionalProperties": true
}

Original tool metadata

{
  "name": "get_indicators",
  "title": "Browse Dataset Indicators",
  "description": "Returns the full list of available indicators for a given dataset.\n\nDatasets often have broader coverage than expected ΓÇö for example, ASI covers\n57 indicators (capital structure, wages, employment, GVA, fuel consumption),\nand GENDER covers 147 indicators across health, education, labor, and crime.\n\nFor PLFS and ASUSE, indicators are grouped by frequency_code:\n  - PLFS frequency_code=1 (Annual): all 8 indicators including wages\n  - PLFS frequency_code=2 (Quarterly): indicators 1-3 only\n  - PLFS frequency_code=3 (Monthly): indicators 1-3 only\n  frequency_code selects the indicator set, not time granularity.\n\nStep 2 of: list_datasets ΓåÆ get_indicators ΓåÆ get_metadata ΓåÆ get_data",
  "inputSchema": {
    "type": "object",
    "required": [
      "dataset"
    ],
    "properties": {
      "level": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "Format": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "series": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "dataset": {
        "type": "string",
        "description": "Dataset name ΓÇö one of: PLFS, CPI, IIP, ISP, ASI, NAS, WPI,\n     ENERGY, AISHE, ASUSE, GENDER, NFHS, ENVSTATS, RBI,\n     NSS77, NSS78, NSS76, NSS75E, NSS79, CPIALRL, HCES, TUS, EC, UDISE, MNRE, NSS80, NSS73.\n     For CPI, IIP, ISP, WPI: returns available base years and frequencies."
      },
      "base_year": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "frequency": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "user_query": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "The user's original question. Captured for telemetry analytics; not echoed back in the response."
      },
      "frequency_code": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "classification_year": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      }
    },
    "additionalProperties": false
  },
  "outputSchema": {
    "type": "object",
    "additionalProperties": true
  },
  "annotations": {
    "readOnlyHint": true,
    "openWorldHint": true,
    "destructiveHint": false
  }
}

get_metadataTitles 93Descriptions 94Inputs 65Annotations 75Outputs 675/100

Title93/100

Get Filter Options & Parameters

The title clearly communicates the tool’s action and subject. Keep it concise.

Description94/100

Returns the valid filter values (states, years, quarters, etc.) for a given dataset and indicator. Filter codes are arbitrary and dataset-specific ΓÇö 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 ΓåÆ get_indicators ΓåÆ get_metadata ΓåÆ get_data

The description explains the capability, when to use it, and what to expect.

Inputs65/100

12 of 15 inputs have descriptions. Add descriptions to the missing inputs, including where to obtain IDs and how to supply values.

dataset

Dataset name (same values as get_indicators).

Clear enough to supply this argument.

indicator_code

Required for: PLFS, NAS, ENERGY, AISHE, ASUSE, GENDER, NFHS, ENVSTATS, RBI, NSS77, NSS78, NSS76, NSS75E, NSS79, CPIALRL, HCES, TUS, EC, UDISE, MNRE, NSS80, NSS73. Not applicable for: CPI, IIP, ISP, ASI, WPI. For RBI, this maps to sub_indicator_code internally.

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

base_year

Required for CPI ("2024"/"2012"/"2010"), IIP ("2011-12"/"2004-05"/"1993-94"), NAS ("2022-23"/"2011-12"), WPI ("2011-12"/"2004-05"/"1993-94"). Not applicable for PLFS, ASI.

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

level

Required for CPI ("Group"/"Item").

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

frequency

Required for IIP ("Annually"/"Monthly").

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

classification_year

Required for ASI ("2008"/"2004"/"1998"/"1987").

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

frequency_code

Required for PLFS and ASUSE. PLFS: 1=Annual, 2=Quarterly bulletin, 3=Monthly. ASUSE: 1=Annual, 2=Quarterly.

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

series

For CPI and NAS only ("Current"/"Back").

Explain the meaning of this value, not just its name.

use_of_energy_balance_code

For ENERGY only (1=Supply, 2=Consumption).

Clear enough to supply this argument.

sub_indicator_code

Not provided

Missing description. Explain what this value means and how to supply it.

survey_code

For NSS76 (1=Disability, 2=Housing & drinking water), NSS75E (2=Education, indicators 43-55), NSS80 (1=Telecom (CMST), 2=Education (CMSE)), and NSS77 AIDIS module (always 1).

Clear enough to supply this argument.

module

For NSS77 only ΓÇö land_livestock (portal nss77) or aidis (portal nss77a). Required when indicator_code overlaps both modules (16-19, 24, 26, 29, 32, 34, 36). Auto-derived for codes unique to one module.

Clear enough to supply this argument.

state_code

For NAS only — required when indicator_code is 23-34 (state-level GSDP/NSDP/GSVA family). Values 01-37, where 37 = All-India aggregate. Comma separated for multiple states. Not applicable when frequency_code=2 (Quarterly) — state-level indicators have Annual data only.

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

Format

Not provided

Missing description. Explain what this value means and how to supply it.

type

Not provided

Missing description. Explain what this value means and how to supply it.

Annotations75/100

Declare idempotentHint based on the tool’s actual behavior.

{
  "readOnlyHint": true,
  "openWorldHint": true,
  "destructiveHint": false
}

Output schema6/100

Declare the result fields and their types in the output schema.

View output schema

{
  "type": "object",
  "additionalProperties": true
}

Original tool metadata

{
  "name": "get_metadata",
  "title": "Get Filter Options & Parameters",
  "description": "Returns the valid filter values (states, years, quarters, etc.) for a\ngiven dataset and indicator.\n\nFilter codes are arbitrary and dataset-specific ΓÇö for example, PLFS\nstate_code 99 means \"All India\", and NAS frequency_code 1 means \"Annual\".\nThese values cannot be inferred or guessed from parameter names alone.\n\nThe returned filter_values and api_params should be used as-is when\ncalling get_data.\n\nStep 3 of: list_datasets ΓåÆ get_indicators ΓåÆ get_metadata ΓåÆ get_data",
  "inputSchema": {
    "type": "object",
    "required": [
      "dataset"
    ],
    "properties": {
      "type": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "level": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for CPI (\"Group\"/\"Item\")."
      },
      "Format": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "module": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "For NSS77 only ΓÇö land_livestock (portal nss77) or aidis (portal nss77a).\n    Required when indicator_code overlaps both modules (16-19, 24, 26, 29, 32, 34, 36).\n    Auto-derived for codes unique to one module."
      },
      "series": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "For CPI and NAS only (\"Current\"/\"Back\")."
      },
      "dataset": {
        "type": "string",
        "description": "Dataset name (same values as get_indicators)."
      },
      "base_year": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for CPI (\"2024\"/\"2012\"/\"2010\"),\n       IIP (\"2011-12\"/\"2004-05\"/\"1993-94\"),\n       NAS (\"2022-23\"/\"2011-12\"),\n       WPI (\"2011-12\"/\"2004-05\"/\"1993-94\").\n       Not applicable for PLFS, ASI."
      },
      "frequency": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for IIP (\"Annually\"/\"Monthly\")."
      },
      "state_code": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "For NAS only — required when indicator_code is 23-34\n        (state-level GSDP/NSDP/GSVA family). Values 01-37, where\n        37 = All-India aggregate. Comma separated for multiple\n        states. Not applicable when frequency_code=2 (Quarterly) —\n        state-level indicators have Annual data only."
      },
      "survey_code": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "For NSS76 (1=Disability, 2=Housing & drinking water), NSS75E\n         (2=Education, indicators 43-55), NSS80 (1=Telecom (CMST), 2=Education (CMSE)),\n         and NSS77 AIDIS module (always 1)."
      },
      "frequency_code": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for PLFS and ASUSE.\n            PLFS: 1=Annual, 2=Quarterly bulletin, 3=Monthly.\n            ASUSE: 1=Annual, 2=Quarterly."
      },
      "indicator_code": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for: PLFS, NAS, ENERGY, AISHE, ASUSE, GENDER,\n            NFHS, ENVSTATS, RBI, NSS77, NSS78, NSS76, NSS75E, NSS79, CPIALRL, HCES, TUS, EC, UDISE, MNRE, NSS80, NSS73.\n            Not applicable for: CPI, IIP, ISP, ASI, WPI.\n            For RBI, this maps to sub_indicator_code internally."
      },
      "sub_indicator_code": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "classification_year": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for ASI (\"2008\"/\"2004\"/\"1998\"/\"1987\")."
      },
      "use_of_energy_balance_code": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "For ENERGY only (1=Supply, 2=Consumption)."
      }
    },
    "additionalProperties": false
  },
  "outputSchema": {
    "type": "object",
    "additionalProperties": true
  },
  "annotations": {
    "readOnlyHint": true,
    "openWorldHint": true,
    "destructiveHint": false
  }
}

get_dataTitles 96Descriptions 80Inputs 97Annotations 75Outputs 1181/100

Title96/100

Fetch Statistical Data

The title clearly communicates the tool’s action and subject. Keep it concise.

Description80/100

Fetches statistical data from a MoSPI dataset. This is the final step of the workflow. It requires filter values from get_metadata ΓÇö 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 ΓåÆ get_indicators ΓåÆ get_metadata ΓåÆ get_data

Describe the returned information so the agent knows whether it will answer the request.

Inputs97/100

Input documentation gives an agent enough context to populate the arguments.

dataset

Dataset name (PLFS, CPI, IIP, ISP, ASI, NAS, WPI, ENERGY, AISHE, ASUSE, GENDER, NFHS, ENVSTATS, RBI, NSS77, NSS78, NSS76, NSS75E, NSS79, CPIALRL, HCES, TUS, EC, UDISE, MNRE, NSS80, NSS73). CPI auto-routes to Group or Item endpoint based on whether filters contain item_code. IIP uses a single endpoint; pass frequency="Annually" or frequency="Monthly" in filters.

Clear enough to supply this argument.

filters

Key-value pairs from get_metadata filter_values. PLFS requires frequency_code (1=Annual, 2=Quarterly, 3=Monthly). NAS requires base_year ("2022-23" or "2011-12"). MNRE: indicator_code (1-5) is mapped to type_of_renewable_energy_code. Pass limit (e.g., "50") to retrieve more than 10 records.

Clear enough to supply this argument.

Annotations75/100

Declare idempotentHint based on the tool’s actual behavior.

{
  "readOnlyHint": true,
  "openWorldHint": true,
  "destructiveHint": false
}

Output schema11/100

Describe the returned fields so an agent can interpret the result.

View output schema

{
  "type": "object",
  "additionalProperties": true
}

Original tool metadata

{
  "name": "get_data",
  "title": "Fetch Statistical Data",
  "description": "Fetches statistical data from a MoSPI dataset.\n\nThis is the final step of the workflow. It requires filter values from\nget_metadata ΓÇö filter codes are arbitrary (e.g., indicator_code=3 means\n\"Unemployment Rate\" in PLFS but something different in other datasets).\n\nAll filter parameters including limit and page go inside the filters dict,\nnot as top-level arguments.\n\nStep 4 of: list_datasets ΓåÆ get_indicators ΓåÆ get_metadata ΓåÆ get_data",
  "inputSchema": {
    "type": "object",
    "required": [
      "dataset",
      "filters"
    ],
    "properties": {
      "dataset": {
        "type": "string",
        "description": "Dataset name (PLFS, CPI, IIP, ISP, ASI, NAS, WPI, ENERGY,\n     AISHE, ASUSE, GENDER, NFHS, ENVSTATS, RBI, NSS77,\n     NSS78, NSS76, NSS75E, NSS79, CPIALRL, HCES, TUS, EC, UDISE, MNRE, NSS80, NSS73).\n     CPI auto-routes to Group or Item endpoint based on\n     whether filters contain item_code.\n     IIP uses a single endpoint; pass frequency=\"Annually\" or\n     frequency=\"Monthly\" in filters."
      },
      "filters": {
        "type": "object",
        "description": "Key-value pairs from get_metadata filter_values.\n     PLFS requires frequency_code (1=Annual, 2=Quarterly, 3=Monthly).\n     NAS requires base_year (\"2022-23\" or \"2011-12\").\n     MNRE: indicator_code (1-5) is mapped to type_of_renewable_energy_code.\n     Pass limit (e.g., \"50\") to retrieve more than 10 records.",
        "additionalProperties": true
      }
    },
    "additionalProperties": false
  },
  "outputSchema": {
    "type": "object",
    "additionalProperties": true
  },
  "annotations": {
    "readOnlyHint": true,
    "openWorldHint": true,
    "destructiveHint": false
  }
}

list_datasetsTitles 99Descriptions 99Inputs 100Annotations 75Outputs 587/100

Title99/100

Discover Available Datasets

The title clearly communicates the tool’s action and subject. Keep it concise.

Description99/100

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 description explains the capability, when to use it, and what to expect.

Inputs100/100

This tool declares no inputs, so argument descriptions are not needed.

No input fields.

Annotations75/100

Declare idempotentHint based on the tool’s actual behavior.

{
  "readOnlyHint": true,
  "openWorldHint": false,
  "destructiveHint": false
}

Output schema5/100

Declare the result fields and their types in the output schema.

View output schema

{
  "type": "object",
  "additionalProperties": true
}

Original tool metadata

{
  "name": "list_datasets",
  "title": "Discover Available Datasets",
  "description": "Returns an overview of all MoSPI statistical datasets with descriptions and coverage.\nThis is the starting point ΓÇö call this first to identify the right dataset.\n\nThe API covers 500+ indicators across employment, prices, industry, national\naccounts, health, education, disability, housing, environment, trade, and more. Each dataset has\nits own indicator codes, filter parameters, and valid values ΓÇö these are not\nstandardized and cannot be inferred or guessed from parameter names alone.\n\nFour-step workflow (each step depends on the previous):\n  1. list_datasets() ΓÇö identify the dataset\n  2. get_indicators(dataset) ΓÇö list available indicators\n  3. get_metadata(dataset, indicator_code) ΓÇö retrieve valid filter values\n  4. get_data(dataset, filters) ΓÇö fetch the data\n\nReturns:\n    dict with 'datasets' (name, description, use_for for each dataset)\n    and 'workflow' (the four-step sequence).",
  "inputSchema": {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  },
  "outputSchema": {
    "type": "object",
    "additionalProperties": true
  },
  "annotations": {
    "readOnlyHint": true,
    "openWorldHint": false,
    "destructiveHint": false
  }
}

Put your MCP to the test

A few tasks worth trying with this server, chosen from its reviewed tools. These have not been run.

01Discover Available DatasetsReturns an overview of all MoSPI statistical datasets with descriptions and coverage.
02Browse Dataset IndicatorsReturns the full list of available indicators for a given dataset.
03Fetch Statistical DataFetches statistical data from a MoSPI dataset.
04Get Filter Options & ParametersReturns the valid filter values (states, years, quarters, etc.) for a

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About this server

Overview

Author: Ministry of Statistics and Programme Implementation (MoSPI), Government of India
Verification: partner
Auth: None (public endpoint)
Category: Data & analytics
Works with: claude
claude-api
claude-code
Docs: Documentation

Tools (4)

step1_know_about_mospi_apistep2_get_indicatorsstep3_get_metadatastep4_get_data

FAQ

MoSPI Data Server setup, tools, quality score, publishing readiness, and alternatives.

How do I add MoSPI Data Server to Claude, ChatGPT, or Cursor?

Add MoSPI Data Server to Claude, ChatGPT, or Cursor by connecting its remote MCP URL in each client's MCP settings. In Claude, add a custom connector. In ChatGPT, add an MCP app. In Cursor, add an MCP server under Settings. The MCP URL is https://mcp.mospi.gov.in/.

Is MoSPI Data Server MCP ready for ChatGPT and Claude?

As of October 6, 2026, MoSPI Data Server scores 100/100 on Manufact's MCP publishing checklist. The scan meets ChatGPT publishing checks and meets Claude publishing checks. Passing these checks does not guarantee marketplace approval.

How clear is MoSPI Data Server's MCP tool documentation?

As of October 6, 2026, MoSPI Data Server scores 76/100 in Manufact's review of tool titles, descriptions, input and output schemas, and behavior annotations. The review covers 4 of 4 discovered tools. The quality score measures documentation clarity; runtime behavior and marketplace readiness require separate checks.

What tools does the MoSPI Data Server MCP server provide?

MoSPI Data Server provides these MCP tools: step1_know_about_mospi_api, step2_get_indicators, step3_get_metadata, and step4_get_data.

What are the best alternatives to MoSPI Data Server?

As of October 20, 2026, alternatives to MoSPI Data Server in data-analytics on the Manufact MCP leaderboard include Epicure, Newsflash, Point Topic, Pricing Optimizer AI, and StatCite.

Does MoSPI Data Server MCP require authentication?

MoSPI Data Server does not require authentication. It is a public MCP endpoint you can connect without logging in.

How can MoSPI Data Server improve its MCP documentation?

get_indicators is the lowest-scoring reviewed tool at 61/100. Declare the result fields and their types in the output schema. Open its review for feedback and a copyable fix prompt, then rerun the documentation review after updating your tool metadata.

Who develops MoSPI Data Server?

MoSPI Data Server is developed by Ministry of Statistics and Programme Implementation (MoSPI), Government of India. It is listed as partner on the Claude connector directory.

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Title93/100

Get Filter Options & Parameters

The title clearly communicates the tool’s action and subject. Keep it concise.

Description94/100

The description explains the capability, when to use it, and what to expect.

Inputs65/100

12 of 15 inputs have descriptions. Add descriptions to the missing inputs, including where to obtain IDs and how to supply values.

dataset

Dataset name (same values as get_indicators).

Clear enough to supply this argument.

indicator_code

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

base_year

Required for CPI ("2024"/"2012"/"2010"), IIP ("2011-12"/"2004-05"/"1993-94"), NAS ("2022-23"/"2011-12"), WPI ("2011-12"/"2004-05"/"1993-94"). Not applicable for PLFS, ASI.

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

level

Required for CPI ("Group"/"Item").

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

frequency

Required for IIP ("Annually"/"Monthly").

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

classification_year

Required for ASI ("2008"/"2004"/"1998"/"1987").

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

frequency_code

Required for PLFS and ASUSE. PLFS: 1=Annual, 2=Quarterly bulletin, 3=Monthly. ASUSE: 1=Annual, 2=Quarterly.

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

series

For CPI and NAS only ("Current"/"Back").

Explain the meaning of this value, not just its name.

use_of_energy_balance_code

For ENERGY only (1=Supply, 2=Consumption).

Clear enough to supply this argument.

sub_indicator_code

Not provided

Missing description. Explain what this value means and how to supply it.

survey_code

For NSS76 (1=Disability, 2=Housing & drinking water), NSS75E (2=Education, indicators 43-55), NSS80 (1=Telecom (CMST), 2=Education (CMSE)), and NSS77 AIDIS module (always 1).

Clear enough to supply this argument.

module

Clear enough to supply this argument.

state_code

Remove validation rules already expressed in this field’s schema; describe its meaning and usage instead.

Format

Not provided

Missing description. Explain what this value means and how to supply it.

type

Not provided

Missing description. Explain what this value means and how to supply it.

Annotations75/100

Declare idempotentHint based on the tool’s actual behavior.

{
  "readOnlyHint": true,
  "openWorldHint": true,
  "destructiveHint": false
}

Output schema6/100

Declare the result fields and their types in the output schema.

View output schema

{
  "type": "object",
  "additionalProperties": true
}

Original tool metadata

{
  "name": "get_metadata",
  "title": "Get Filter Options & Parameters",
  "description": "Returns the valid filter values (states, years, quarters, etc.) for a\ngiven dataset and indicator.\n\nFilter codes are arbitrary and dataset-specific ΓÇö for example, PLFS\nstate_code 99 means \"All India\", and NAS frequency_code 1 means \"Annual\".\nThese values cannot be inferred or guessed from parameter names alone.\n\nThe returned filter_values and api_params should be used as-is when\ncalling get_data.\n\nStep 3 of: list_datasets ΓåÆ get_indicators ΓåÆ get_metadata ΓåÆ get_data",
  "inputSchema": {
    "type": "object",
    "required": [
      "dataset"
    ],
    "properties": {
      "type": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "level": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for CPI (\"Group\"/\"Item\")."
      },
      "Format": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "module": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "For NSS77 only ΓÇö land_livestock (portal nss77) or aidis (portal nss77a).\n    Required when indicator_code overlaps both modules (16-19, 24, 26, 29, 32, 34, 36).\n    Auto-derived for codes unique to one module."
      },
      "series": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "For CPI and NAS only (\"Current\"/\"Back\")."
      },
      "dataset": {
        "type": "string",
        "description": "Dataset name (same values as get_indicators)."
      },
      "base_year": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for CPI (\"2024\"/\"2012\"/\"2010\"),\n       IIP (\"2011-12\"/\"2004-05\"/\"1993-94\"),\n       NAS (\"2022-23\"/\"2011-12\"),\n       WPI (\"2011-12\"/\"2004-05\"/\"1993-94\").\n       Not applicable for PLFS, ASI."
      },
      "frequency": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for IIP (\"Annually\"/\"Monthly\")."
      },
      "state_code": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "For NAS only — required when indicator_code is 23-34\n        (state-level GSDP/NSDP/GSVA family). Values 01-37, where\n        37 = All-India aggregate. Comma separated for multiple\n        states. Not applicable when frequency_code=2 (Quarterly) —\n        state-level indicators have Annual data only."
      },
      "survey_code": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "For NSS76 (1=Disability, 2=Housing & drinking water), NSS75E\n         (2=Education, indicators 43-55), NSS80 (1=Telecom (CMST), 2=Education (CMSE)),\n         and NSS77 AIDIS module (always 1)."
      },
      "frequency_code": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for PLFS and ASUSE.\n            PLFS: 1=Annual, 2=Quarterly bulletin, 3=Monthly.\n            ASUSE: 1=Annual, 2=Quarterly."
      },
      "indicator_code": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for: PLFS, NAS, ENERGY, AISHE, ASUSE, GENDER,\n            NFHS, ENVSTATS, RBI, NSS77, NSS78, NSS76, NSS75E, NSS79, CPIALRL, HCES, TUS, EC, UDISE, MNRE, NSS80, NSS73.\n            Not applicable for: CPI, IIP, ISP, ASI, WPI.\n            For RBI, this maps to sub_indicator_code internally."
      },
      "sub_indicator_code": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null
      },
      "classification_year": {
        "anyOf": [
          {
            "type": "string"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "Required for ASI (\"2008\"/\"2004\"/\"1998\"/\"1987\")."
      },
      "use_of_energy_balance_code": {
        "anyOf": [
          {
            "type": "integer"
          },
          {
            "type": "null"
          }
        ],
        "default": null,
        "description": "For ENERGY only (1=Supply, 2=Consumption)."
      }
    },
    "additionalProperties": false
  },
  "outputSchema": {
    "type": "object",
    "additionalProperties": true
  },
  "annotations": {
    "readOnlyHint": true,
    "openWorldHint": true,
    "destructiveHint": false
  }
}

Manufact

Server metadata

Protocol

Tools

MCP Apps

Tool documentation quality

Title99/100

Description80/100

Inputs19/100

Annotations75/100

Output schema4/100

Title93/100

Description94/100

Inputs65/100

Annotations75/100

Output schema6/100

Title96/100

Description80/100

Inputs97/100

Annotations75/100

Output schema11/100

Title99/100

Description99/100

Inputs100/100

Annotations75/100

Output schema5/100

Put your MCP to the test

About this server

Overview

Related MCP servers

FAQ

Not your MCP?

Server metadata

Protocol

Tools

MCP Apps

Tool documentation quality

Title99/100

Description80/100

Inputs19/100

Annotations75/100

Output schema4/100

Title93/100

Description94/100

Inputs65/100

Annotations75/100

Output schema6/100

Title96/100

Description80/100

Inputs97/100

Annotations75/100

Output schema11/100

Title99/100

Description99/100

Inputs100/100

Annotations75/100

Output schema5/100

Put your MCP to the test

About this server

Overview

Related MCP servers

FAQ

Not your MCP?