Claude-Patent-Creator
Claude Patent Creator 是一个基于AI的专利创建与分析系统,专为Claude Code设计。它整合了RAG技术,能快速检索MPEP、USC等专利法规,并利用BigQuery访问数千万专利进行现有技术搜索。系统还提供自动化合规性检查(如35 USC 112),并支持图表生成,旨在显著提升专利专业人士的工作效率。
git clone https://github.com/RobThePCGuy/Claude-Patent-Creator.gitBefore / After 效果对比
1 组传统专利申请流程耗时漫长,需手动查阅大量法规文件,耗费数周进行现有技术检索,且人工审查权利要求合规性易出错,效率低下。
借助AI系统,法规检索秒级响应,现有技术搜索覆盖亿级专利,自动化合规检查提供具体反馈,大幅缩短申请周期,提升专利撰写质量。
description SKILL.md
Claude Patent Creator
An AI-powered patent creation and analysis system for Claude Code.
I built this because I needed to file a patent myself. I used AI to build the system, used the system to file the patent, and it worked. Now it's open source so anyone can use it, whether you're a developer exploring AI tooling or a patent professional looking to speed up your workflow.
In plain terms, this tool lets you:
- Search patent regulations instantly. Ask a question about MPEP, 35 USC, 37 CFR, EPC, or PCT rules and get the relevant sections in under a second, with citations.
- Find prior art across 100M+ patents. Search Google's BigQuery patent database by keywords, CPC/IPC codes, or full-text queries. Link related patents across jurisdictions with family search.
- Check your claims for compliance. Run your draft claims through automated analysis for USPTO (35 USC 112(b)) or EPO (Art. 84 EPC) and get specific feedback on definiteness, two-part form, and structure.
- Review your full application. Specification adequacy, formalities, required sections — checked against USPTO, EPO, or PCT standards.
- Search EP patents with full text. Get full claims and description text for European patents via the EPO OPS API (not available in BigQuery).
- Generate patent diagrams. Block diagrams, flowcharts, and system architectures in patent style, no design tools needed.
- Draft a complete patent application. A guided workflow that walks you through the whole process, from invention disclosure to filing-ready documents — for USPTO or EPO filing.
Table of Contents
- Quick Start
- What Can I Actually Do With This?
- How It Works
- Installation Options
- CLI Commands
- MCP Tools Reference
- Skills, Agents, and Slash Commands
- Configuration
- Requirements
- Architecture
- Performance
- Known Issues
- Glossary
- Roadmap
- Contributing
- Credits
- License
Quick Start
Pick the path that fits your setup. All three get you to the same place.
Option A: Claude Code Plugin (Easiest)
If you're already using Claude Code, this is the fastest way in:
# Add the marketplace and install
/plugin marketplace add RobThePCGuy/Claude-Patent-Creator
/plugin install claude-patent-creator-standalone@claude-patent-creator
# Run setup
/claude-patent-creator-standalone:setup-patent-system
Option B: One-Line Install
pip install git+https://github.com/RobThePCGuy/Claude-Patent-Creator.git && patent-creator setup
This handles everything automatically: installs dependencies, detects your GPU, downloads MPEP PDFs (~500MB), builds the search index, and registers the MCP server with Claude Code. Restart Claude Code when it finishes.
Option C: Manual Install
git clone https://github.com/RobThePCGuy/Claude-Patent-Creator.git
cd Claude-Patent-Creator
# Optional: use a virtual environment
python -m venv venv
source venv/bin/activate # Linux/macOS
venv\Scripts\activate # Windows
pip install -e .
patent-creator setup
Verify It Worked
After any install path, run:
patent-creator health
You should see a status report showing which components are ready. If something's off, the output will tell you what to fix.
What Can I Actually Do With This?
Here are some real examples. You can type these directly in Claude Code and the right skill or tool kicks in automatically.
| What you want to do | What to say | What happens |
|---|---|---|
| Find the MPEP rule on claim definiteness | "Search MPEP for claim definiteness requirements" | Hybrid search returns the most relevant MPEP sections with citations |
| Look for prior art | "Search for patents about neural network training filed in 2024" | BigQuery searches 100M+ patents and returns matching results |
| Check your claims | "Review these claims for 35 USC 112(b) compliance" | Automated analysis flags indefinite terms, missing antecedent basis, structural issues |
| Review a full application | /full-review | Runs claims + specification + formalities checks in parallel |
| Create a patent from scratch | /create-patent | Guided 6-phase workflow, takes 55-80 min, produces a complete filing package |
| Generate a diagram | "Create a block diagram showing the system architecture" | Generates a patent-style Graphviz diagram |
| Search prior art thoroughly | "Conduct a prior art search for [your invention]" | Automated novelty and freedom-to-operate analysis |
How It Works
The system has two modes that can work independently or together:
MCP Server is the engine. It exposes 20+ tools that any MCP-compatible client (Claude Code, Claude Desktop, etc.) can call programmatically. These tools handle search, analysis, and diagram generation.
Claude Code Plugin adds the interactive layer. Skills activate automatically based on what you're doing. Agents handle long-running tasks in the background. Slash commands give you quick access to common workflows.
Under the hood, patent regulation search uses a hybrid approach: FAISS vector search finds semantically similar content, BM25 lexical search catches exact terminology matches, and a cross-encoder reranker sorts the combined results by relevance. Patent search goes through Google BigQuery's public patent dataset.
You (Claude Code) ──> MCP Server ──> Search / Analysis / Diagrams
│
┌──────────────┼──────────────┐
v v v
MPEP/USC/CFR BigQuery Graphviz
(hybrid RAG) (100M+ patents) (diagrams)
Installation Options
- Installs Python package dependencies
- Detects your hardware (NVIDIA GPU, Apple Silicon, or CPU-only)
- If a GPU is detected, uninstalls CPU-only PyTorch and installs the GPU version
- Restarts the setup process with GPU-enabled PyTorch
- Downloads MPEP, 35 USC, and 37 CFR PDFs (~500MB) from the USPTO
- Builds the hybrid search index (FAISS + BM25) with GPU acceleration if available
- Registers the MCP server with Claude Code
python -m venv venv
source venv/bin/activate # Linux/macOS
venv\Scripts\activate # Windows
pip install git+https://github.com/RobThePCGuy/Claude-Patent-Creator.git && patent-creator setup
If you go this route, remember to activate the venv before running any manual commands. Claude Code handles activation automatically.
claude --plugin-dir ./Claude-Patent-Creator
This loads the plugin directly from your local checkout without installing from the marketplace.
CLI Commands
patent-creator setup # Full setup wizard (downloads, builds index, registers MCP)
patent-creator health # System health check (shows what's working and what isn't)
patent-creator status # Same as health
patent-creator verify-config # Check Claude Code MCP configuration
patent-creator serve # Run the MCP server manually
patent-creator rebuild-index # Rebuild the MPEP search index
patent-creator download-mpep # Download MPEP PDFs only
patent-creator download-all # Download all sources (MPEP + 35 USC + 37 CFR)
patent-creator check-bigquery # Test BigQuery connection
patent-creator download-patents # Download PatentsView corpus (9.2M+ patents)
patent-creator build-patent-index # Build patent search index
patent-creator patents-status # Show patent corpus status
MCP Tools Reference
Search
| Tool | What it does |
|---|---|
search_mpep | Hybrid RAG search across MPEP, 35 USC, and 37 CFR with filters |
get_mpep_section | Pull full content of a specific MPEP section |
search_patents_bigquery | Search 100M+ patents by keyword |
get_patent_bigquery | Get full details on a specific patent |
search_patents_by_cpc_bigquery | Search by CPC classification code |
search_uspto_api | Search via the USPTO API |
get_uspto_patent | Get patent details from USPTO |
get_recent_uspto_patents | Pull recent filings |
search_prior_art | Automated prior art discovery |
Analysis
| Tool | What it does |
|---|---|
review_patent_claims | 35 USC 112(b) compliance check (definiteness, antecedent basis, structure) |
review_specification | 35 USC 112(a) adequacy check (written description, enablement, best mode) |
check_formalities | MPEP 608 compliance (abstract, title, drawings, required sections) |
Generation
| Tool | What it does |
|---|---|
render_diagram | Generate patent-style diagrams from Graphviz DOT code |
create_flowchart | Build a flowchart from a list of steps and connections |
create_block_diagram | Build a block diagram from components and relationships |
add_diagram_references | Add patent reference numbers to an existing SVG diagram |
get_diagram_templates | List available diagram templates |
System
| Tool | What it does |
|---|---|
get_index_stats | Search index statistics |
check_bigquery_status | BigQuery configuration status |
check_diagram_tools_status | Graphviz availability |
check_patent_corpus_status | Patent corpus status |
check_uspto_api_status | USPTO API connectivity |
get_patent_details | Combined patent retrieval across sources |
setup_claude_config | Copy .claude configuration (skills, commands) to a project directory |
Skills, Agents, and Slash Commands
Skills (activate automatically)
You don't need to call these directly. Just describe what you want to do and the right skill kicks in.
| Skill | When it activates | What it brings |
|---|---|---|
| setup-assistant | Installing, configuring, or troubleshooting | Full setup lifecycle guidance |
| patent-reviewer | Reviewing a complete application for compliance | Comprehensive review (claims + spec + formalities) |
| patent-claims-analyzer | Reviewing claims specifically for 35 USC 112(b) | Deep-dive claims analysis (definiteness, antecedent basis, structure) |
| patent-search | Searching patents or prior art | BigQuery + PatentsView API search workflows |
| bigquery-patent-search | Quick BigQuery-only patent search | Keyword, CPC, and patent detail retrieval across 100M+ patents |
| mpep-search | Finding MPEP sections or regulations | Hybrid RAG search |
| patent-diagram-generator | Creating technical diagrams | Flowcharts, block diagrams, system architectures via Graphviz |
| patent-application-creator | Drafting a patent application interactively | Guided end-to-end workflow (prior art, claims, spec, diagrams, compliance) |
| prior-art-search | Novelty or freedom-to-operate analysis | 7-step prior art discovery methodology |
| index-manager | Building or rebuilding the search index | MPEP index lifecycle management |
| development-assistant | Adding features or creating tools | Development workflows and patterns |
| troubleshooting-assistant | Something's broken | Systematic 6-step diagnostics |
| testing-assistant | Running tests or validation | Test suite execution |
Agents (long-running, work independently)
These run in the background while you keep working on other things.
| Agent | What it does | How long | Output |
|---|---|---|---|
| patent-creator | Drafts a complete USPTO-ready application | 55-80 min | Specification, claims, abstract, diagrams, validation report |
| prior-art-searcher | Comprehensive prior art search | 15-30 min | Patentability report, top 10 prior art, claim strategy, IDS list |
To use them: "Create a patent for [your invention], use the patent-creator agent"
Slash Commands
/create-patent # Complete patent creation workflow (55-80 min)
/search-prior-art # Prior art search with novelty analysis
/full-review # Parallel review (claims + spec + formalities)
/review-claims # Claims-only 35 USC 112(b) analysis
/review-specification # Specification-only 35 USC 112(a) analysis
/review-formalities # MPEP 608 formalities check
Configuration
Environment Variables
Create a .env file in the project root (see .env.example):
# Required for BigQuery patent search
GOOGLE_CLOUD_PROJECT=your-project-id
# Optional: EPO OPS API (for EP patent full-text search)
# Free registration at https://developers.epo.org
EPO_OPS_KEY=your-consumer-key
EPO_OPS_SECRET=your-consumer-secret
# Optional API keys (for HyDE query expansion)
ANTHROPIC_API_KEY=sk-ant-...
OPENAI_API_KEY=sk-...
# Optional settings
PATENT_LOG_LEVEL=INFO
PATENT_LOG_FORMAT=human
PATENT_ENABLE_METRICS=true
PATENT_MPEP_USE_HYDE=false
PATENT_MPEP_DEVICE=gpu
PATENT_OPERATION_TIMEOUT=300
BigQuery gives you access to 100M+ worldwide patents. It requires a Google Cloud project with billing enabled (the public patent dataset itself is free to query within BigQuery's free tier).
# 1. Install Google Cloud SDK
# https://cloud.google.com/sdk/docs/install
# 2. Authenticate
gcloud auth application-default login
# 3. Set quota project (replace with your project ID)
gcloud auth application-default set-quota-project your-project-id
# 4. Set the environment variable
export GOOGLE_CLOUD_PROJECT="your-project-id" # Linux/macOS
$env:GOOGLE_CLOUD_PROJECT="your-project-id" # Windows PowerShell
# 5. Test it
patent-creator check-bigquery
Git Bash is required for the claude mcp add command on Windows. Install Git for Windows and set the path:
# In your .env file
CLAUDE_CODE_GIT_BASH_PATH=C:\Program Files\Git\bin\bash.exe
Use forward slashes in MCP config paths. The setup wizard handles this, but if you're configuring manually:
# Correct
claude mcp add ... -- "C:/Users/YourName/venv/Scripts/python.exe"
# Wrong (will fail)
claude mcp add ... -- "C:\Users\YourName\venv\Scripts\python.exe"
Requirements
Minimum
- Python: 3.9 - 3.13 (3.14 is experimental)
- RAM: 8GB
- Disk: ~2GB (MPEP PDFs + search index)
Optional (but recommended)
- GPU: NVIDIA with CUDA 12.8 (makes indexing 5-10x faster) or Apple Silicon (2-3x faster)
- Google Cloud: Project with BigQuery enabled (for patent search)
- Graphviz: System package (for diagram generation)
| Package | Version | Purpose |
|---|---|---|
| mcp | >=1.21.0 | MCP server framework |
| sentence-transformers | >=5.1.2, <6.0.0 | Text embeddings |
| faiss-cpu | >=1.13.0 | Vector similarity search |
| numpy | >=1.26.0, <3.0.0 | Array operations |
| rank-bm25 | >=0.2.2 | Lexical search |
| transformers | >=4.57.1, <5.0.0 | HuggingFace models |
| google-cloud-bigquery | >=3.38.0 | Patent search |
| pydantic | >=2.10.0 | Data validation |
| graphviz | >=0.21 | Diagram generation |
| PyMuPDF | >=1.26.0 | PDF processing |
See pyproject.toml for the complete list.
Architecture
claude-patent-creator/
├── .claude-plugin/ # Plugin manifest and marketplace config
├── mcp_server/ # Core MCP server
│ ├── server.py # FastMCP entry point
│ ├── mpep_search.py # Hybrid RAG search engine
│ ├── bigquery_search.py # BigQuery patent search
│ ├── claims_analyzer.py # 35 USC 112(b) analyzer
│ ├── specification_analyzer.py # 112(a) analyzer
│ ├── formalities_checker.py # MPEP 608 checker
│ ├── diagram_generator.py # Graphviz diagrams
│ ├── tools/ # MCP tool definitions
│ └── index/ # FAISS + BM25 index (git-ignored)
├── skills/ # Claude Code skills (13)
├── agents/ # Autonomous agents (10)
├── commands/ # Slash commands (11)
├── hooks/ # Event-driven automation
├── scripts/ # Testing and utilities
├── docs/ # Additional documentation
├── pdfs/ # Downloaded MPEP PDFs (git-ignored)
└── CLAUDE.md # Full project documentation
For the complete architecture documentation, development workflows, and troubleshooting guides, see CLAUDE.md.
Performance
| Operation | Time | Notes |
|---|---|---|
| MPEP Search | 50-200ms | Hybrid FAISS + BM25 |
| BigQuery Patent Search | 1-3 sec | 100M+ patents |
| USPTO API | 500ms - 2s | Rate-limited by USPTO |
| Index Build (GPU) | 3-5 min | NVIDIA CUDA 12.8 |
| Index Build (Apple Silicon) | 8-12 min | MPS acceleration |
| Index Build (CPU) | 25-35 min | No GPU |
Resource usage: the loaded search index takes about 2-4GB of RAM and the index files are 500MB-1GB on disk. If you have a GPU, it'll use 1-2GB of VRAM for acceleration.
Known Issues
This project is a work in progress. Most features work, but expect some rough edges. Contributions, issues, and PRs are welcome.
Things to be aware of:
- PyTorch install order matters. Install PyTorch before
sentence-transformers, or you'll end up with CPU-only PyTorch even on a GPU system. The setup wizard handles this, but it can bite you on manual installs. - BigQuery requires a Google Cloud project with billing enabled. The patent data itself is free to query within the BigQuery free tier.
- Some diagram types need Graphviz installed as a system package (not just the Python bindings).
- HyDE query expansion requires API keys (Anthropic or OpenAI). It's optional and off by default.
- Windows users need Git Bash for the
claude mcp addcommand. See Windows setup notes.
See CLAUDE.md for the full troubleshooting guide.
Glossary
If you're coming from the development side and patent terminology is new (or vice versa), here's a quick reference:
| Term | What it means |
|---|---|
| MPEP | Manual of Patent Examining Procedure. The handbook patent examiners use at the USPTO. Think of it as the rulebook. |
| 35 USC | Title 35 of the United States Code. The federal patent statutes. |
| 37 CFR | Title 37 of the Code of Federal Regulations. The rules that implement the patent statutes. |
| USPTO | United States Patent and Trademark Office. The agency that grants patents. |
| CPC | Cooperative Patent Classification. A system for categorizing patents by technology area. |
| Prior Art | Anything publicly available before your filing date that's relevant to your invention. Finding it is how you figure out if your idea is actually new. |
| 112(a) | The section of patent law requiring your application to fully describe and enable the invention. |
| 112(b) | The section requiring your claims to be definite and clear. |
| MPEP 608 | The section covering formalities like abstract length, title format, and drawing requirements. |
| RAG | Retrieval Augmented Generation. Instead of relying only on what the AI was trained on, it searches a database first and uses those results to give a better answer. |
| FAISS | Facebook AI Similarity Search. A fast way to find similar text by comparing mathematical representations of meaning. |
| BM25 | A text search algorithm that matches exact words and phrases. Works alongside FAISS to catch things vector search might miss. |
| MCP | Model Context Protocol. A standard for connecting AI tools to AI models. It's how this system talks to Claude. |
| IDS | Information Disclosure Statement. A form listing prior art references you need to disclose to the USPTO. |
Roadmap
- Complete implementation of all MCP tools
- Evaluation metrics for RAG search performance
- Support for international patent offices (EPO, WIPO/PCT)
- Web interface for non-Claude Code users
- Claim dependency graph visualization
- Automated obviousness analysis (35 USC 103)
- Patent portfolio analysis tools
- Integration with patent drafting software
Contributing
This project is open to contributions. Since it's a work in progress, expect breaking changes and incomplete documentation. Issues and PRs are welcome.
See CONTRIBUTING.md for the development setup, branch naming, commit conventions, and code style guide.
Credits
Open Source Dependencies
This project builds on excellent open source work: FastMCP, FAISS (Meta AI Research), Sentence Transformers (UKP Lab), HuggingFace Transformers, PyTorch, rank-bm25, PyMuPDF, Graphviz, Pydantic, and Google Cloud BigQuery.
Data Sources
MPEP, 35 USC, and 37 CFR are published by the USPTO. Patent data comes from Google BigQuery's patents-public-data dataset (100M+ patents). Embedding models are BGE-base-en-v1.5 (BAAI) and MS-MARCO MiniLM-L-6-v2 (Microsoft).
Trademark Notice
"USPTO" is a registered trademark of the United States Patent and Trademark Office. This project isn't affiliated with, endorsed by, or sponsored by the USPTO.
Project Status
This project is in beta. I'm actively working on it, but not everything is polished and some features may not work as described. If you run into issues, open one on GitHub and I'll take a look.
For detailed documentation: CLAUDE.md | For security issues: SECURITY.md
License
MIT License. See LICENSE for details.
Built with Claude Code. The code is the output, but the real work is deciding what needs to exist and how the pieces fit together.
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