Analytics API integration

The Analytics API provides structured access to key performance indicators related to innovation activity, including publication trends, company presence, and funding levels. It enables you to quantify interest, track growth, and assess maturity in specific technologies, organizations, or topics. Ideal for market analysis, technology scouting, and strategic planning, this API delivers data-driven insights to help you identify emerging opportunities and evaluate innovation potential.

Learn more about these indicators in this article.

The API returns data in JSON format.

Note: You may experience timeouts if queries are too broad, for example, retrieving publication trends over long time spans at high resolution (e.g., 10 years in monthly intervals), or requesting too many KPIs for a broad topic.

Getting started 

Before integrating the Documents API, you must authenticate and generate a token. You can test the API using the API Demo page, where you can also download a JavaScript demo app to test it directly in your browser. Additionally, you can use the MCP server to test MAPEGY APIs.

KPI

Retrieve KPI (see type) by query

Make Requests

To interact with the API, you must send HTTP GET or POST requests to the API endpoint using the default content type.
Every request needs a token.

  • API Endpoint: https://api.mapegy.com
  • Content-Type: application/x-www-form-urlencoded
  • Route:  /KPI
  • Required parameter: q. Defines the query structure for retrieving documents.
    Find an example below. You can also learn more about the q parameter here.
{
    "format_version": "1.6.0",
    "data": {
        "topics": [
            [
                "artificial intelligence",
                "deep learning"
            ]
        ],
        "not_topics": [],
        "organizations": [],
        "not_organizations": []
    }
}

Optional Parameters
  • type: Restrict results to specific indicators. Just add them as comma-separated values. 
    • NB_NEWS: Estimated total number of news articles published about the topic or organization in the past 10 years; indicates public visibility.
    • NB_PATENT: Estimated total number of patent publications related to the topic or organization in the past 10 years; indicates overall patenting activity.
    • NB_SCIENCE: Estimated total number of research publications related to the topic or authored by the organization in the past 10 years; indicates research activity.
    • RATE_RECENT_ NEWS: The publication rate of news articles generated over the most recent year.
    • RATE_RECENT_ SCIENCE: The publication rate of research papers over the most recent year.
    • RATE_RECENT_ PATENT: The publication rate of patents over recent active years (accounting for publication lag).
    • RATE_PAST_ PATENT: The historical baseline average of patent publications from earlier years (omitting the 3-year publication gap).
    • GROWTH_NEWS: Compares the past year's news publication rate to the historical average to measure media growth trends.
    • GROWTH_SCIENCE: Compares the past year's research publications to historical averages to evaluate scientific momentum.
    • GROWTH_PATENT: Compares recent patent activity against historical averages while omitting the past 3 years to account for the patent publication gap.
    • NB_COMPANY: Estimated total number of established companies (excluding startups) active in the space over the past 10 years; indicates market saturation and technological maturity.
    • NB_STARTUP: Estimated total number of active startups operating in the space over the past 10 years; indicates early-stage market adoption.
    • FUNDING_STARTUP: Estimated total funding received by startups in the past 10 years; indicates investor confidence and market potential.
    • FUNDING_RESEARCH: Estimated total funding received by research projects (past or near future); indicates technology push and institutional priorities.
  • include: Specifies which response fields to retrieve. Simply list the desired response fields, separated by commas. To view all available fields, run a query without specifying this parameter.

Example:
  • Route: /KPI/?q=
  • Method: GET or POST
  • Content-Type: application/x-www-form-urlencoded
  • Mandatory parameters: q (query), token
  • Optional parameters used: type
  • Example GET request: KPI?q=%7B%22format_version%22%3A%221.6.0%22,%22data%22%3A%7B%22topics%22%3A%5B%5B%22artificial%20intelligence%22,%22deep%20learning%22%5D%5D,%22not_topics%22%3A%5B%5D,%22organizations%22%3A%5B%5D,%22not_organizations%22%3A%5B%5D%7D%7D&token=fr9Ch_2BDFI-rBR6edo0Lb-0JRVP6lBb5Fb7p4FYND0Xnlk_2NpNNcJ1IAYlO3SL&type=NB_NEWS
  • Example response:
{
  "kpi": {
    "NB_DOCS": 1116183,
    "NB_NEWS": 1116183
  },
  "meta": {
    "contextual": {
      "NB_NEWS": {
        "alpha": 0.05,
        "algorithm": "sample",
        "date_init": "2016-08-20",
        "error_est": 9241
      }
    }
  }
}

Facets 

Get document counts broken by year (Facets/Documents/Year), by quarter (Facets/Documents/Quarter) or by month (Facets/Documents/Month).

Make Requests

To interact with the API, you must send HTTP GET or POST requests to the API endpoint using the default content type.
Every request needs a token.

  • API Endpoint: https://api.mapegy.com
  • Content-Type: application/x-www-form-urlencoded
  • Route:
    • Facets/Documents/Year
    • Facets/Documents/Quarter
    • Facets/Documents/Month
Required parameters
  • q. Defines the query structure for retrieving documents. You can also learn more about the q parameter here.
  • type. NEWS, NEWS__STARTUP, NEWS__FORECAST, NEWS__FUNDING, NEWS__CONFERENCE, NEWS__LEGAL, NEWS__M&A, NEWS__REPORT, NEWS__PRODUCT, NEWS__SIGNAL, SCIENCE, SCIENCE__ARTICLE, SCIENCE__BOOK, SCIENCE__CONFERENCE, PATENT
Optional parameters
  • country_code: Add two letter country codes to focus on specific countries. Separate values by commas.
  • date_from: Set earlier date using the following format: YYYY-MM-DD. 
  • date_to: Set latest date using the following format: YYYY-MM-DD.
  • publisher: Publisher name for science. 
  • source: News source or science series, 
  • tag: NEWS tag name. 
  • patent_granted: Set true or false to filter by patent grant type.
  • limit:  Restricts the number of results, just enter a number from 1 to 500.
  • include: Specifies which response fields to retrieve. Simply list the desired response fields, separated by commas. To view all available fields, run a query without specifying this parameter.

Example:
  • Route: /Facets/Documents/Year?q=
  • Method: GET or POST
  • Content-Type: application/x-www-form-urlencoded
  • Mandatory parameters: q (query), type, token
  • Example GET request:
    http://facets/Documents/Year?q=%7B%22format_version%22%3A%221.6.0%22,%22data%22%3A%7B%22topics%22%3A%5B%5B%22artificial%20intelligence%22,%22deep%20learning%22%5D%5D,%22not_topics%22%3A%5B%5D,%22organizations%22%3A%5B%5D,%22not_organizations%22%3A%5B%5D%7D%7D&type=NEWS
    &token=fr9Ch_2BDFI-rBR6edo0Lb-0JRVP6lBb5Fb7p4FYND0Xnlk_2NpNNcJ1IAYlO3SL
  • Example response:
[
  {
    "count": 151460,
    "facet": "2026-01-01",
    "count_normalized": 183724.2,
    "count_extrapolated": 320840.5,
    "count_normalized_extrapolated": 220608.3
  },
  {
    "count": 242678,
    "facet": "2025-01-01",
    "count_normalized": 163611,
    "count_extrapolated": null,
    "count_normalized_extrapolated": null
  },
  {
    "count": 206517,
    "facet": "2024-01-01",
    "count_normalized": 168668.1,
    "count_extrapolated": null,
    "count_normalized_extrapolated": null
  },
  {
    "count": 178838,
    "facet": "2023-01-01",
    "count_normalized": 122780.6,
    "count_extrapolated": null,
    "count_normalized_extrapolated": null
  },
  {
    "count": 50192,
    "facet": "2022-01-01",
    "count_normalized": 54673.6,
    "count_extrapolated": null,
    "count_normalized_extrapolated": null
  },
  {
    "count": 49066,
    "facet": "2021-01-01",
    "count_normalized": 59811.8,
    "count_extrapolated": null,
    "count_normalized_extrapolated": null
  },
  {
    "count": 65328,
    "facet": "2020-01-01",
    "count_normalized": 57013,
    "count_extrapolated": null,
    "count_normalized_extrapolated": null
  },
  {
    "count": 62775,
    "facet": "2019-01-01",
    "count_normalized": 53895.3,
    "count_extrapolated": null,
    "count_normalized_extrapolated": null
  },
  {
    "count": 51358,
    "facet": "2018-01-01",
    "count_normalized": 122369.3,
    "count_extrapolated": null,
    "count_normalized_extrapolated": null
  },
  {
    "count": 45669,
    "facet": "2017-01-01",
    "count_normalized": 98998.3,
    "count_extrapolated": null,
    "count_normalized_extrapolated": null
  },
  {
    "count": 12262,
    "facet": "2016-01-01",
    "count_normalized": 30597.6,
    "count_extrapolated": null,
    "count_normalized_extrapolated": null
  }
]
Related articles