Patent Intelligence API

Patent data infrastructure for builders.

Search patent records by technical query, title, parties, classification or date range. Choose the fields your app receives and page through structured results, or use hybrid semantic search and AI evidence analysis. REST endpoints and MCP tools share one API key format and transparent quotas. Indian patents are the default; worldwide publications are available where enabled.

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Search coverage manifest

illustrative hybrid response
Corpusindian-patent-journal
JurisdictionIN
Documents indexed160,000+
Semantic coverage99%+
Search modehybrid-semantic-text
Embedding modeltext-embedding-3-small

Every search response includes this manifest. When the corpus grows or a new jurisdiction comes online, your integration sees the change in the response — no polling, no changelog to watch.

Element-wise evidence verdict

per feature × per patent
Phase-change thermal storage panelpresent
Photovoltaic charging of storagepartial
Predictive pre-cooling controllerabsent
Door-opening schedule integrationunknown

Each verdict carries a verbatim quote and the field it was found in. An “unknown” means insufficient evidence in the available text — not “probably novel”. Quality flags report when the evidence basis is thin.

Coverage

India + worldwide where enabled

Search

Hybrid + structured filters

AI analysis

Feature extraction & evidence mapping

Protocols

REST + MCP for AI agents

Use cases

What people build on top of it.

The API is used by legal tech platforms, IP analytics tools, R&D workflow automation, and AI agents that need patent intelligence as a building block — not a destination.

Patent landscape analytics

Build technology maps, monitor competitive filings, and track assignee activity across the Indian patent jurisdiction — programmatically, on your own schedule.

Prior art screening

Integrate prior-art screening into your invention intake workflow. Submit disclosures, get structured features and ranked prior art — before a human analyst touches the case.

IP due diligence

Feed feature-level evidence into M&A, licensing, and freedom-to-operate workflows. Every verdict carries a verbatim quote and source field — ready for citation.

Novelty assessment automation

Run the full extract → search → map pipeline from code. Build element-wise novelty matrices that compare each invention feature against multiple prior-art references.

AI agent workflows

Connect Claude, Cursor, or your own agent stack via MCP. Agents autonomously research prior art, evaluate patentability, or generate structured reports — with the same data and quotas as REST.

Legal tech platforms

Embed patent intelligence into case management, prosecution tracking, or filing systems. Structured JSON responses with stable schemas, versioned endpoints, and predictable rate-limit headers.

Workflow

Three calls. Disclosure in, evidence matrix out.

The API is designed around how novelty analysis actually works: decompose the invention, find what exists, then build an element-wise evidence chart. Each call produces structured output that feeds directly into the next — no reformatting, no copy-paste between tools.

  1. 1

    Describe the invention in plain English

    extract

    Send a disclosure (40–20,000 characters) to the feature extraction endpoint. It runs the same AI normalization stage as the full PatentNest novelty pipeline — atomic technical features, novelty-focus candidates, a ready-to-use prior-art search query, and CPC/IPC classification hints. No patent vocabulary required from your side.

  2. 2

    Search the corpus with the suggested query

    search

    Use the AI-suggested query — or write your own — to run hybrid semantic and full-text search across the patent corpus. Results come back ranked with composite, semantic, and text relevance scores. Every response includes a coverage manifest: corpus, jurisdiction, document count, and the share that is semantically indexed. A negative result is a measured signal, not a guess.

  3. 3

    Map features against shortlisted patents

    map

    For each shortlisted result, submit the features and the publication number. Each feature is classified as present, partial, absent, or unknown — with a verbatim quote from the patent text and the field it was found in (title, abstract, or claims). You get the evidence, not a summary of it.

Endpoints

Four endpoints. No SDK required.

Standard REST with JSON request/response and bearer auth. Every endpoint returns structured data with a request ID, duration, and rate-limit headers. Errors use stable, machine-readable codes. Import the OpenAPI 3.1 spec into Postman, Swagger UI, or any code generator.

Patent search and filters

passes
POST /api/v1/patents/search

Search by technical query, title, applicant, inventor, identifiers, classification, or filing, publication and recorded grant date ranges. Choose returned fields. Use structured mode to paginate and sort individual publications, or hybrid mode for up to 50 ranked results. Every response includes a coverage manifest.

Patent record lookup

passes
GET /api/v1/patents/{publicationNumber}

Retrieve a patent record by publication number and choose returned fields with the fields parameter. Case and separators are normalized automatically.

AI feature extraction

passes
POST /api/v1/analysis/features

AI analysis of a plain-English invention disclosure. Returns atomic technical features with per-feature confidence and type classification, novelty-focus candidates, a retrieval-optimized search query, and CPC/IPC classification hints.

Element-wise evidence mapping

passes
POST /api/v1/analysis/feature-mapping

Classifies each submitted feature (1–12) as present, partial, absent, or unknown against one patent record — with a verbatim quote and the field it was sourced from. Returns quality flags for low evidence, ambiguous abstracts, and language mismatch.

Search controls

Choose the records and fields your app needs.

Use the same search endpoint for a ranked technical shortlist or structured patent records. Combine filters, select response fields, and control how results are returned.

Combine patent filters

Search title, abstract, publication/application number, applicant, inventor and classification. Add inclusive filing, publication or recorded grant date ranges. Criteria combine with AND; entries in an array combine with OR.

Select returned fields

Request just the title, applicants, dates or other public fields your app uses. Omit fields for the full public record. Publication number and source attribution are always included.

Page and sort structured results

Structured mode accepts filters without an AI query, returns up to 50 publications per page, and supports date/title sorting. Continue with pagination.nextOffset up to the documented offset cap.

Keep semantic search available

Send a technical query for hybrid semantic and text ranking, with the same filters and field selection. Hybrid results form a relevance-ranked shortlist; structured mode provides pagination.

Filter reference and request examples →

Data

Structured records, not summaries.

The public record supplies structured applicants, inventor names, classification codes, available dates and source provenance. Select the fields your app needs, or receive the full public record. Hybrid search adds relevance scores; structured search adds pagination.

Publication & application numbers

Canonical publication number, raw application number, country code, and kind code. Normalized and deduplicated across journal issues.

Title, abstract, and full text

Complete title and abstract as published. Full claims text available for AI analysis endpoints (feature mapping evidence is quoted verbatim from it).

Structured applicants

Array of applicant objects — name, address, and sequence number. Not a concatenated string. Ready for assignee landscape analysis.

Inventors and classifications

Inventor list as published. IPC and CPC classification codes for technology landscape mapping, trend analysis, and cross-jurisdiction comparison.

Filing, publication and recorded grant dates

Filter filingDate, publicationDate and grantDate using inclusive date ranges. Grant dates are returned only when explicitly recorded in stored IP India metadata; unavailable dates are null.

Extraction confidence and source provenance

Extraction confidence where available, source name, journal document and page where known, and licence/attribution for worldwide data. Identity and source remain present when you select response fields.

Relevance scoring (search)

Hybrid search includes composite, semantic and text-match scores plus matched fields. Structured search instead returns individual publications with date/title sorting and pagination.

Coverage manifest (search)

Corpus name, jurisdiction, total document count, semantic coverage percentage, search mode, and embedding model. Returned with every search so your integration always knows what was searched.

AI agents

Native MCP support for the agent era.

POST /api/v1/mcp exposes all four operations as MCP tools over streamable HTTP. Same bearer keys, same quotas, same structured data — but now Claude, Cursor, or your own agent stack calls them directly without glue code. Sessions are stateless. Protocol versions 2025-06-18, 2025-03-26, and 2024-11-05 are supported.

Claude Desktop and Claude Code

Add the MCP config to your Claude settings. Four patent tools appear alongside your other tools. Your agent searches prior art, extracts features, and builds evidence charts in a single conversation.

Cursor, Windsurf, and AI IDEs

Any IDE that speaks MCP can connect. Patent intelligence becomes part of a coding or research workflow without leaving the editor.

Custom agent platforms

Standard JSON-RPC over streamable HTTP. Build agents that autonomously screen invention disclosures, monitor competitive filings, or generate prior-art reports.

REST for everything else

No agent framework needed. Standard HTTP in any language. The MCP transport is there for tools that speak it — everyone else uses the four REST endpoints.

MCP server configuration

{
  "mcpServers": {
    "patentnest": {
      "type": "http",
      "url": "https://patentnest.ai/api/v1/mcp",
      "headers": {
        "Authorization": "Bearer pn_live_your_key"
      }
    }
  }
}

Trust and limits

Transparent metering. Your disclosures stay yours.

Rate limits are per-minute, daily, and monthly — all returned in every response header. AI analysis has a separate daily budget. Rejected requests never consume a credit. Submitted invention disclosures are processed and forgotten — never stored as text, never used for training.

Request quotas

Per-minute, daily, and monthly budgets per client. Headers on every response: RateLimit-Limit, RateLimit-Remaining, X-RateLimit-Daily-Remaining, X-RateLimit-Monthly-Remaining. HTTP 429 includes Retry-After.

Analysis budget

The two AI analysis endpoints run full LLM inference — they have their own daily credit pool. A credit is charged only after validation passes and the model starts. A 400 or 404 costs nothing.

Data confidentiality

Submitted disclosures produce the response, then are not retained. Request logs store hashes and metadata, never invention text. No model training on your data. Request bodies capped at 256 KB.

Coverage

India by default. Worldwide where enabled.

Search the Indian corpus from IP India Patent Journal publications, or request other patent offices through the jurisdictions parameter where worldwide access is enabled. The same endpoints support both coverage options.

Indian Patent Journal corpus

Indian patent publications extracted from journal PDFs, with source provenance on each record. The coverage manifest reports the corpus document count and semantic indexing percentage when those figures are available.

Worldwide patent publications

Request office codes such as US, EP or WO, or all offices with ["*"]. Worldwide records come from Google Patents Public Data, cover publications from 2000 onward, and refresh quarterly. Reproduce the source attribution when displaying these records.

Documentation

Complete reference, OpenAPI spec, and quick start.

API reference documentationOpenAPI 3.1 specification

Get API access for your platform.

API keys are provisioned per client with configurable rate limits. Tell us what you're building and we'll set up access, walk through the endpoints, or provision a sandbox environment for your integration.

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