Axiomatic AI▌
by axiomatic-ai
Extract plot data from images with Axiomatic AI. Use advanced web plot digitizer features for scientific imaging and ana
Provides six specialized servers for scientific and engineering workflows including photonic circuit design with gdsfactory integration, document processing with advanced OCR, plot data extraction from images, equation composition and analysis, PDF annotation with contextual analysis, and model fitting with optimization capabilities.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Engineers working on photonic circuit design
- / Researchers processing scientific documents and papers
- / Scientists extracting data from published plots and figures
- / Academics analyzing mathematical models and equations
capabilities
- / Design photonic circuits with gdsfactory integration
- / Extract text from documents using advanced OCR
- / Extract data points from plot images
- / Compose and analyze mathematical equations
- / Annotate PDFs with contextual analysis
- / Fit mathematical models with optimization
what it does
Provides six specialized servers for scientific workflows including photonic circuit design with gdsfactory, OCR document processing, plot data extraction, equation analysis, PDF annotation, and model fitting.
about
Axiomatic AI is a community-built MCP server published by axiomatic-ai that provides AI assistants with tools and capabilities via the Model Context Protocol. Extract plot data from images with Axiomatic AI. Use advanced web plot digitizer features for scientific imaging and ana It is categorized under ai ml, analytics data.
how to install
You can install Axiomatic AI in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Axiomatic AI is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Axiomatic MCP Servers
MCP (Model Context Protocol) servers that provide AI assistants with access to the Axiomatic_AI Platform - a suite of advanced tools for scientific computing, document processing, and photonic circuit design.
🚀 Quickstart
1. Check system requirements
- Python
- Install here
- uv
- Install here
- Recommended not to install in conda (see Troubleshooting)
- install extra packages (optional)
- If you wish to use the AxPhotonicsPreview, you will need to install extra dependencies before continuing. After installing uv, run
uv tool install "axiomatic-mcp[pic]".
- If you wish to use the AxPhotonicsPreview, you will need to install extra dependencies before continuing. After installing uv, run
2. Install your favourite client
3. Get an API key
You will receive an API key by email shortly after filling the form. Check your spam folder if it doesn't arrive.
4. Install Axiomatic Operators (all except AxPhotonicsPreview)
<details> <summary><strong>⚡ Claude Code</strong></summary>claude mcp add axiomatic-mcp --env AXIOMATIC_API_KEY=your-api-key-here -- uvx --from axiomatic-mcp all
</details>
<details>
<summary><strong>🔷 Cursor</strong></summary>
</details>
<details>
<summary><strong>🤖 Claude Desktop</strong></summary>
- Open Claude Desktop settings → Developer → Edit MCP config
- Add this configuration:
{
"mcpServers": {
"axiomatic-mcp": {
"command": "uvx",
"args": ["--from", "axiomatic-mcp", "all"],
"env": {
"AXIOMATIC_API_KEY": "your-api-key-here"
}
}
}
}
- Restart Claude Desktop
Follow the MCP install guide and use the standard configuration above. See the official instructions here: Gemini CLI MCP Server Guide
{
"axiomatic-mcp": {
"command": "uvx",
"args": ["--from", "axiomatic-mcp", "all"],
"env": {
"AXIOMATIC_API_KEY": "your-api-key-here"
}
}
}
</details>
<details>
<summary><strong>🌬️ Windsurf</strong></summary>
Follow the Windsurf MCP documentation. Use the standard configuration above.
{
"axiomatic-mcp": {
"command": "uvx",
"args": ["--from", "axiomatic-mcp", "all"],
"env": {
"AXIOMATIC_API_KEY": "your-api-key-here"
}
}
}
</details>
<details>
<summary><strong>🧪 LM Studio</strong></summary>
Click the button to install:
</details> <details> <summary><strong>💻 Codex</strong></summary>Note: After installing via the button, open LM Studio MCP settings and add:
"env": { "AXIOMATIC_API_KEY": "your-api-key-here" }
Create or edit the configuration file ~/.codex/config.toml and add:
[mcp_servers.axiomatic-mcp]
command = "uvx"
args = ["--from", "axiomatic-mcp", "all"]
env = { AXIOMATIC_API_KEY = "your-api-key-here" }
For more information, see the Codex MCP documentation
</details> <details> <summary><strong>🌊 Other MCP Clients</strong></summary>Use this server configuration:
{
"command": "uvx",
"args": ["--from", "axiomatic-mcp", "all"],
"env": {
"AXIOMATIC_API_KEY": "your-api-key-here"
}
}
</details>
Note: This installs all tools except for AxPhotonicsPreview under one server. If you experience other issues, try individual servers instead.
Reporting Bugs
Found a bug? Please help us fix it by creating a bug report.
Connect on Discord
Join our Discord to engage with other engineers and scientists using Axiomatic Operators. Ask for help, discuss bugs and features, and become a part of the Axiomatic community!
Troubleshooting
Cannot install in Conda environment
It's not recommended to install axiomatic operators inside a conda environment. uv handles seperate python environments so it is safe to run "globally" without affecting your existing Python environments
Server not appearing in Cursor
- Restart Cursor after updating MCP settings
- Check the Output panel (View → Output → MCP) for errors
- Verify the command path is correct
The "Add to cursor" button does not work
We have seen reports of the cursor window not opening correctly. If this happens you may manually add to cursor by:
- Open cursor
- Go to "Settings" > "Cursor Settings" > "MCP & Integration"
- Click "New MCP Server"
- Add the following configuration:
{
"mcpServers": {
"axiomatic-mcp": {
"command": "uvx --from axiomatic-mcp all",
"env": {
"AXIOMATIC_API_KEY": "YOUR API KEY"
},
"args": []
}
}
}
Multiple servers overwhelming the LLM
Install only the domain servers you need. Each server runs independently, so you can add/remove them as needed.
API connection errors
- Verify your API key is set correctly
- Check internet connection
Tools not appearing
If you experience any issues such as tools not appearing, it may be that you are using an old version and need to clear uv's cache to update it.
uv cache clean
Then restart your MCP client (e.g. restart Cursor).
This clears the uv cache and forces fresh downloads of packages on the next run.
Individual servers
You may find more information about each server and how to install them individually in their own READMEs.
🖌️ AxEquationExplorer
Compose equation of your interest based on information in the scientific paper.
📄 AxDocumentParser
Convert PDF documents to markdown with advanced OCR and layout understanding.
📝 AxDocumentAnnotator
Create intelligent annotations for PDF documents with contextual analysis, equation extraction, and parameter identification.
🔬 AxPhotonicsPreview
Design photonic integrated circuits using natural language descriptions. Additional requirements are needed, please refer to Check system requirements
📊 AxPlotToData
Extract numerical data from plot images for analysis and reproduction.
⚙️ AxModelFitter
Fit parametric models or digital twins to observational data using advanced statistical analysis and optimization algorithms.
Requesting Features
Have an idea for a new feature? We'd love to hear it! Submit a feature request and:
- Describe the problem your feature would solve
- Explain your proposed solution
- Share any alternatives you've considered
- Provide specific use cases
Support
- Join our Discord Server
- Issues: GitHub Issues
FAQ
- What is the Axiomatic AI MCP server?
- Axiomatic AI is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Axiomatic AI?
- This profile displays 27 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.7★★★★★27 reviews- ★★★★★Kofi Sanchez· Dec 20, 2024
Axiomatic AI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Luis Abebe· Dec 8, 2024
Useful MCP listing: Axiomatic AI is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Luis Garcia· Nov 27, 2024
Strong directory entry: Axiomatic AI surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Camila Mensah· Oct 18, 2024
I recommend Axiomatic AI for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Li Srinivasan· Oct 2, 2024
Strong directory entry: Axiomatic AI surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Piyush G· Sep 21, 2024
Useful MCP listing: Axiomatic AI is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Chen Brown· Sep 21, 2024
We wired Axiomatic AI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Evelyn Huang· Sep 9, 2024
Axiomatic AI is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Oshnikdeep· Sep 1, 2024
Axiomatic AI has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Yusuf Harris· Aug 28, 2024
We wired Axiomatic AI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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