The Documents API grants access to an extensive collection of innovation-related publications, including news, patents, scientific papers, standards, research projects, and project descriptions.
Learn more about these publications in this article.

By integrating the Documents API into your application, you can retrieve structured, filtered content based on specific search queries. Designed for applications that rely on diverse, high-quality publications, this API helps analyze trends, track competitor developments, and monitor advancements across various fields.

Additionally, the .documents/analyze endpoint allows you to process datasets of up to 500 documents for a specific use case, returning a compact, AI-driven analysis along with the most critical documents.

The API returns data in JSON format.

‍

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.

‍

Documents

Get documents by query, ordered by highest relevance.

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: /Documents/?q=

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:

• topic_id: Filter results by related topic IDs (comma-separated values).
• player_id: Filter results by related player IDs (comma-separated values).
• doc_id: All documents that match this ID(s) will be returned, ignoring all other filters, and no matter how well they match the query. This can be used to update KPIs of bookmarked documents.
• type: Restrict results to specific document types (e.g., NEWS, NEWS__STARTUP, NEWS__FORECAST). Just add them as comma-separated values. 
• highlight: Set 'true' to highlight matched keywords in title and abstract with <mark>keyword</mark> (returns HTML). Default: 'false' (returns TEXT).
• country_code: Add two letter country codes to focus on specific patent offices. Separate values by commas. 
• publisher: Publisher name, for SCIENCE, STANDARD, PROJECT_DESCR
• source: NEWS source or SCIENCE series.
• tag: NEWS tag name.
• patent_granted: Set 'true' or 'false' to filter by patent grant type‍
• date_from: Set earlier date using the following format: YYYY-MM-DD. ‍
• date_to: Set latest date using the following format: YYYY-MM-DD.
• ‍order: Sort by most relevant (default), newest or recently added to our database. ‍
• days: Number of past days within which the item was integrated into the InnovationGraph.‍
• limit: Restricts the number of documents, just enter a number from 1 to 30.‍‍
• 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.

How are retrieved publications prioritized?
Articles are automatically ranked and returned in order of relevance based on your specific search query. The system prioritizes the highest-quality, most relevant content first, meaning top-ranked results will always contain the strongest contextual matches.
You can use the order parameter to sort results by most relevant, newest or recently added to our database.

Does the API support page-based pagination (e.g., "Page 2") or dual sorting by freshness and relevance?
‍Traditional page-based pagination (such as requesting "Page 2") and combined sort parameters (fresh-AND-relevant) are not currently supported. To retrieve larger datasets without missing or duplicating records, we recommend using a timestamp/date-based pagination strategy—splitting successive API requests across specific date ranges.

‍

Example: Access the Documents API with a valid token:

• Route: /Documents/?q=
• Method: GET or POST
• Content-Type: application/x-www-form-urlencoded
• Mandatory parameters: q (query), token
• Optional parameters used: type, country_code, date_from
• Example GET request:
  Documents/?q=%7B%22format_version%22%3A%221.6.0%22,%22data%22%3A%7B%22semantic%22%3A%22%22,%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=PATENT&country_code=US&date_from=2024-01-01 ‍
• ‍Example response:
  

[
  {
    "title": "Method and system for adaptive virtual broadcasting of digital content",
    "doc_id": 192430740,
    "topics": {
      "SECTOR": [
        {
          "term": "IT & Telecommunications",
          "topic_id": 1487261,
          "score_relevance": 1.709
        }
      ],
      "SCIENCE": [
        {
          "term": "Computer Networks and Communications",
          "topic_id": 5782254,
          "score_relevance": 1.709
        },
        {
          "term": "Media Technology",
          "topic_id": 5782110,
          "score_relevance": 1.6
        },
        {
          "term": "Hardware and Architecture",
          "topic_id": 5782163,
          "score_relevance": 0.608
        }
      ],
      "INDUSTRY": [
        {
          "term": "Communication",
          "topic_id": 1487182,
          "score_relevance": 1
        }
      ],
      "TECHNOLOGY": [
        {
          "term": "Digital communication",
          "topic_id": 1487227,
          "score_relevance": 1
        }
      ]
    },
    "abstract": "The virtual broadcast system of the present invention optimizes the routing of digital content among nodes along overlay networks that are dynamically reconfigured based upon forecasts of...",
    "doc_type": "PATENT",
    "web_links": {
      "homepage": "https://worldwide.espacenet.com/patent/search?q=PN=US2016192029A1"
    },
    "patent_meta": {
      "events": [],
      "granted": "true",
      "publn_nr": [
        "US2016192029A1",
        "US9769536B2"
      ],
      "epodoc_nr": "14848268",
      "inventors": [
        {
          "person_name": "Bergstrom, Mattias",
          "person_address": "Puerto de la Cruz",
          "person_ctry_code": "ES",
          "person_name_orig_lg": "Bergstrom, Mattias"
        }
      ],
      "applicants": [
        {
          "person_name": "Bergstrom, Mattias",
          "person_address": "Puerto de la Cruz",
          "person_ctry_code": "ES",
          "person_name_orig_lg": "Bergstrom, Mattias"
        },
        {
          "person_name": "SYSTEM73, INC.",
          "person_address": "Dallas,TX",
          "person_ctry_code": "US",
          "person_name_orig_lg": "SYSTEM73, INC."
        }
      ],
      "prior_date": "2014-12-26",
      "country_code": "US",
      "patent_office": "US",
      "docdb_family_id": 55066402,
      "docdb_family_size": 18,
      "nb_citing_docdb_fam": 75
    },
    "doc_sub_type": [],
    "expert_names": [
      "Mattias, Bergstrom"
    ],
    "doc_timestamp": "2015-09-08 00:00:00 UTC",
    "language_code": "EN",
    "score_relevance": 0.3799,
    "player_sub_types": [
      "COMPANY",
      "INVENTOR"
    ],
    "web_links_broken": {},
    "inserted_timestamp": "2018-01-15 10:18:33 UTC",
    "organization_names": [
      "System73, Inc."
    ]
  }
]

‍

‍

Documents/Analyze

documents/analyze lets you feed in up to 500 publications and get back a quick, AI-generated summary focused on your specific use case. It cuts through the noise by highlighting the key takeaways and picking out the most important documents for you.

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: /Documents/Analyze/

Required parameters:

• ‍q. Defines the query structure for retrieving documents.
  Find an example below. You can also learn more about the q parameter here. 
• type: The specific analysis template or use case you select to guide the AI, shaping how it summarizes the dataset and which insights it prioritizes. See below the available use cases.
  
  • Top 5 categories (NEWS__TOP_CATEGORIES, RESEARCH__TOP_CATEGORIES, PATENTS__TOP_CATEGORIES): Summarizes the top 5 innovation categories within news, research papers, or patents.
  • Application identification (NEWS__APPLICATION_AREAS, PROJECTS__APPLICATION_AREAS, RESEARCH__APPLICATION_AREAS, PATENTS__APPLICATION_AREAS): Identifies the most relevant application areas and their benefits, grouped by industry.
  • Technologies with High TRL (NEWS__HIGH_TRL_TECHNOLOGIES, RESEARCH__HIGH_TRL_TECHNOLOGIES, PATENTS__HIGH_TRL_TECHNOLOGIES, PROJECTS__HIGH_TRL_TECHNOLOGIES): Extracts technologies with a Technology Readiness Level (TRL) above 5.
  • Material identification (NEWS__MATERIALS_IDENTIFICATION, RESEARCH__MATERIALS_IDENTIFICATION, PATENTS__MATERIALS_IDENTIFICATION): Finds materials actively used to solve, enable, improve, or characterize the topic (or those developed/applied by a specific organization).
  • Technology and concept identification (NEWS__EMERGING_TECHNOLOGIES, RESEARCH__EMERGING_TECHNOLOGIES, PATENTS__EMERGING_TECHNOLOGIES, PROJECTS__EMERGING_TECHNOLOGIES): Identifies new, distinct technical innovations at the material, device, method, or system design level.
  • Threat detection (NEWS__THREAT_DETECTION): Pinpoints potential risks and operational or market threats mentioned in news coverage.
  • Sentiment analysis (NEWS__SENTIMENT_ANALYSIS): Evaluates whether overall news media coverage leans positive, neutral, or negative.
  • Legal updates (NEWS__LEGAL_UPDATES): Summarizes key regulatory changes, legal updates, and compliance shifts.
  • M&A (NEWS__M&A_UPDATES): Highlights major mergers, acquisitions, and investment activities.
  • Startup identification (NEWS__STARTUP_UPDATES): Tracks key startup announcements, launches, and related ecosystem activities.
  • Product innovations (NEWS__PRODUCT_INNOVATIONS): Pinpoints notable new product releases and product-level enhancements.
  • Innovation trends (NEWS__INNOVATION_TRENDS): Summarizes emerging technology trends and broader strategic advancements.
  • R&D Grants (NEWS__R&D_GRANTS_FUNDING): Details active grants, public funding, and funding initiatives for R&D projects.

Example: Access documents/analyze with a valid token:

• Route: /Documents/Analyze
• Method: GET or POST
• Content-Type: application/x-www-form-urlencoded
• Mandatory parameters: q (query), type
• Example GET request: /Documents/Analyze?type=NEWS__TOP_CATEGORIES&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=b6c7ZuPSDgWDnFHXiRxHyhSTLIYLlVIMG0RCLO95WAMfjeDH4qLA6M3DgIGb6NQM‍
• ‍Example response:

{
  "categories": [
    {
      "category": "AI Market Growth and Enterprise Applications",
      "summary": "This category encompasses news about the rapid expansion of the artificial intelligence market, including enterprise AI deployments, infrastructure investments, and sector-specific growth forecasts, highlighting the increasing adoption and integration of AI technologies across industries.",
      "related_items": [
        {
          "name": "Artificial Intelligence Market Growth Accelerates with Enterprise AI, Machine Learning, and AI Infrastructure Investments",
          "url": "http://www.marketsandmarketsblog.com/artificial-intelligence-market-growth-accelerates-with-enterprise-ai-machine-learning-and-ai-infrastructure-investments.html",
          "doc_id": 2011168037
        },
        {
          "name": "Artificial Intelligence Market Trends: AI Infrastructure, Foundation Models, and Enterprise Applications Lead Growth",
          "url": "http://www.marketsandmarketsblog.com/artificial-intelligence-market-trends-ai-infrastructure-foundation-models-and-enterprise-applications-lead-growth.html",
          "doc_id": 1984662808
        },
        {
          "name": "Artificial Intelligence Market Growth Supported by Expanding Agentic AI Deployments",
          "url": "http://www.marketsandmarketsblog.com/artificial-intelligence-market-growth-supported-by-expanding-agentic-ai-deployments.html",
          "doc_id": 1992867590
        },
        {
          "name": "AI Market Size to Surpass USD 4,216.29 Billion by 2035 Amid Rapid Expansion of Generative AI and Enterprise Automation",
          "url": "https://timestech.in/ai-market-size-to-surpass-usd-4216-29-billion-by-2035-amid-rapid-expansion-of-generative-ai-and-enterprise-automation/",
          "doc_id": 1974081739
        },
        {
          "name": "Artificial Intelligence Market Trends 2025: Generative AI, AI Chips, and Cloud AI Platforms Fuel Industry Expansion",
          "url": "http://www.marketsandmarketsblog.com/artificial-intelligence-market-trends-2025-generative-ai-ai-chips-and-cloud-ai-platforms-fuel-industry-expansion.html",
          "doc_id": 1967723045
        }
      ]
    },
    {
      "category": "Deep Learning and AI Technical Innovations",
      "summary": "This category covers advancements and educational resources in deep learning and related AI methodologies, including tutorials, technical explanations, and applications of deep learning models in various domains such as health and environmental monitoring.",
      "related_items": [
        {
          "name": "PyCharm: PyTorch Tutorial for Deep Learning",
          "url": "https://blog.jetbrains.com/pycharm/2026/07/pytorch-tutorial-for-deep-learning/",
          "doc_id": 2023898665
        },
        {
          "name": "CNNs, RNNs, and Transformers Explained: A Mental Model for Key Deep Learning Concepts",
          "url": "https://www.freecodecamp.org/news/cnns-rnns-and-transformers-explained-a-mental-model-for-key-deep-learning-concepts/",
          "doc_id": 2008588305
        },
        {
          "name": "Deep Learning Closes Wildfire Data Gaps",
          "url": "https://scienmag.com/deep-learning-closes-wildfire-data-gaps/",
          "doc_id": 1974019347
        },
        {
          "name": "Deep Learning Reveals Brain Networks in Alcohol Disorder",
          "url": "https://scienmag.com/deep-learning-reveals-brain-networks-in-alcohol-disorder/",
          "doc_id": 1972713181
        },
        {
          "name": "Deep Learning Market to Reach $1,963.25 Billion by 2035 as Generative AI and Enterprise Automation Drive Massive AI Investments | Research by SNS Insider",
          "url": "https://www.globenewswire.com/news-release/2026/06/19/3314691/0/en/Deep-Learning-Market-to-Reach-1-963-25-Billion-by-2035-as-Generative-AI-and-Enterprise-Automation-Drive-Massive-AI-Investments-Research-by-SNS-Insider.html",
          "doc_id": 1991092327
        }
      ]
    },
    {
      "category": "AI in Healthcare and Medical Applications",
      "summary": "This category focuses on the integration of AI and deep learning in healthcare, showcasing innovations in diagnostics, disease detection, personalized medicine, and AI-driven healthcare market growth.",
      "related_items": [
        {
          "name": "Artificial Intelligence in Healthcare Market worth $194.79 billion by 2031  MarketsandMarkets™",
          "url": "https://orthospinenews.com/2026/06/23/artificial-intelligence-in-healthcare-market-worth-194-79-billion-by-2031-marketsandmarkets/?utm_source=rss&utm_medium=rss&utm_campaign=artificial-intelligence-in-healthcare-market-worth-194-79-billion-by-2031-marketsandmarkets",
          "doc_id": 1994130672
        },
        {
          "name": "Artificial Intelligence in Early Breast Cancer Detection: A Systematic Review of Innovations in Preventive Women’s Healthcare"
        },
        {
          "name": "Deep Learning Predicts Antidepressant Response from Electronic Health Records",
          "url": "https://scienmag.com/deep-learning-predicts-antidepressant-response-from-electronic-health-records/",
          "doc_id": 2006536285
        },
        {
          "name": "FDA Grants 510(k) Clearance to GE HealthCare's True Definition DL Software",
          "url": "http://www.itnonline.com/content/fda-grants-510k-clearance-ge-healthcares-true-definition-dl-software",
          "doc_id": 1939180708
        },
        {
          "name": "AI Diagnoses Brain Tumors in Minutes Rather Than Weeks",
          "url": "https://scienmag.com/ai-diagnoses-brain-tumors-in-minutes-rather-than-weeks/",
          "doc_id": 1983878406
        }
      ]
    },
    {
      "category": "Ethical, Social, and Policy Implications of AI",
      "summary": "This category addresses the societal, ethical, and governance challenges posed by AI, including trust issues, policy debates, academic integrity concerns, and calls for global safeguards and responsible AI use.",
      "related_items": [
        {
          "name": "The AI Trust Paradox: Businesses Are Racing Ahead, but Consumers Are Hesitating",
          "url": "https://securityaffairs.com/195915/ai/the-ai-trust-paradox-businesses-are-racing-ahead-but-consumers-are-hesitating.html",
          "doc_id": 2014717875
        },
        {
          "name": "Artificial Intelligence and the Future of Humanity: Nobel Laureates Call for Global Safeguards",
          "url": "https://www.ipsnews.net/2026/07/artificial-intelligence-and-the-future-of-humanity-nobel-laureates-call-for-global-safeguards/",
          "doc_id": 2013700428
        },
        {
          "name": "Schools Debate AI Tools Like ChatGPT as Concerns Over Academic Integrity Grow",
          "url": "https://www.webpronews.com/schools-debate-ai-tools-like-chatgpt-as-concerns-over-academic-integrity-grow/",
          "doc_id": 1992311937
        },
        {
          "name": "Bipartisan Bill Proposes Federal AI Agency with Safety and Transparency Rules",
          "url": "https://www.webpronews.com/bipartisan-bill-proposes-federal-ai-agency-with-safety-and-transparency-rules/",
          "doc_id": 1981904226
        },
        {
          "name": "State Attorneys General Probe OpenAI Over ChatGPT Risks to Children",
          "url": "https://www.webpronews.com/state-attorneys-general-probe-openai-over-chatgpt-risks-to-children/",
          "doc_id": 1987180331
        }
      ]
    },
    {
      "category": "AI in Industry and Robotics",
      "summary": "This category highlights the application of AI and robotics in various industries including manufacturing, logistics, retail, and defense, emphasizing automation, AI-powered robots, and AI-driven operational improvements.",
      "related_items": [
        {
          "name": "Artificial Intelligence Robots Market to Reach USD 229.7B by 2035",
          "url": "https://timestech.in/artificial-intelligence-robots-market-to-reach-usd-229-7b-by-2035/",
          "doc_id": 2004697228
        },
        {
          "name": "C.H. Robinson and Gap Reveal Two Winning AI Strategies in Retail and Logistics",
          "url": "https://www.webpronews.com/c-h-robinson-and-gap-reveal-two-winning-ai-strategies-in-retail-and-logistics/",
          "doc_id": 1986527647
        },
        {
          "name": "Artificial Intelligence in Warfare: The New Era of Autonomous Defense Systems",
          "url": "http://www.marketsandmarketsblog.com/artificial-intelligence-in-warfare-the-new-era-of-autonomous-defense-systems.html",
          "doc_id": 1968559530
        },
        {
          "name": "GM Swaps Hundreds of IT Staff for AI Experts in Blunt Skills Overhaul",
          "url": "https://www.webpronews.com/gm-swaps-hundreds-of-it-staff-for-ai-experts-in-blunt-skills-overhaul/",
          "doc_id": 1962404393
        },
        {
          "name": "AI Reshaping Astrophysics: Threat to Jobs or New Era of Human-AI Collaboration?",
          "url": "https://www.webpronews.com/ai-reshaping-astrophysics-threat-to-jobs-or-new-era-of-human-ai-collaboration/",
          "doc_id": 1984654936
        }
      ]
    }
  ]
}