Examplary MCP Server
Provides AI assistants with access to Examplary's exam management platform, enabling users to create and manage exams, generate questions from materials, grade student responses, and collaborate in workspaces through 60+ API endpoints.
README
Examplary MCP Server
A Model Context Protocol (MCP) server for Examplary, providing AI assistants with access to the Examplary exam management API.
Features
- 60+ API Endpoints - Full access to Examplary's exam management capabilities
- Auto-generated Tools - All API operations automatically available as MCP tools via OpenAPI specification
- Secure Authentication - User-specific API key authentication
- Cross-platform - Works on macOS, Linux, and Windows via UV runtime
- One-click Installation - Install as a .mcpb package in Claude Desktop
What is Examplary?
Examplary is an AI-powered exam management platform that helps educators:
- Create and manage exams with AI assistance
- Generate questions from source materials
- Grade student responses automatically
- Organize content in collaborative workspaces
- Share resources via publisher libraries
Installation
Option 1: Claude Desktop (.mcpb package)
- Download the latest
examplary-mcp.mcpbfrom the releases page - Open Claude Desktop
- Go to Settings → Extensions
- Click "Install Extension" and select the downloaded .mcpb file
- When prompted, enter your Examplary API key
Option 2: Manual Installation
-
Clone this repository:
git clone https://github.com/examplary/examplary-mcp.git cd examplary-mcp -
Install UV (if not already installed):
curl -LsSf https://astral.sh/uv/install.sh | sh -
Run the server:
export EXAMPLARY_API_KEY="your-api-key-here" uv run src/server.py
Getting Your API Key
- Log in to Examplary
- Navigate to Account → Developer
- Click "Generate New API Key"
- Copy the API key and save it securely
Note: Keep your API key secret. Never commit it to version control or share it publicly.
Usage
Once installed in Claude Desktop, you can ask Claude to interact with Examplary:
- "Create a new exam about Python programming"
- "List all my exams"
- "Generate questions from this document"
- "Get the results for exam ID 12345"
- "Create a new organization workspace"
The MCP server provides access to all Examplary API endpoints, including:
Exam Management
- Create, read, update, and delete exams
- Duplicate exams
- Export to PDF or Word
- AI-powered question generation
Question Bank
- Store and organize reusable questions
- Public and private question types
- Bulk import from various formats
Student Sessions
- Create grading sessions
- Scan documents for answers
- AI-powered grading and feedback
- Accept or reject grading suggestions
Organizations & Collaboration
- Manage workspaces
- Invite team members
- Organize exams in folders
Publisher Library
- Browse public content
- Share exam templates
- Discover featured resources
Development
Project Structure
examplary-mcp/
├── manifest.json # MCPB manifest configuration
├── pyproject.toml # Python dependencies
├── src/
│ ├── __init__.py
│ └── server.py # Main MCP server
├── .mcpbignore # Files excluded from .mcpb package
└── .github/
└── workflows/
└── release.yml # Automated release workflow
Local Development
-
Install dependencies:
uv pip install -e . -
Set your API key:
export EXAMPLARY_API_KEY="your-api-key" -
Run the server:
uv run src/server.py
Building the .mcpb Package
To build the .mcpb package manually:
zip -r examplary-mcp.mcpb \
manifest.json \
pyproject.toml \
src/ \
icon.png \
-x "*.pyc" -x "__pycache__/*" -x ".git/*"
Testing
The server uses stdio transport for communication with Claude Desktop. To test locally:
- Run the server with your API key set
- The server will start and listen for MCP protocol messages on stdin
- Send MCP requests via stdin and receive responses on stdout
API Rate Limits
Examplary enforces rate limits on certain operations:
- Exam generation: 3 requests per 60 seconds
- Question operations: 10 requests per 60 seconds
- Other endpoints: Standard rate limiting applies
Security
- API keys are stored securely by Claude Desktop
- All communication uses HTTPS
- API keys can be revoked at any time from the Examplary dashboard
- Never share your API key or commit it to version control
Support
- Examplary Documentation: https://developers.examplary.ai
- Examplary Support: support@examplary.ai
- Issues: https://github.com/examplary/examplary-mcp/issues
License
MIT License - see LICENSE file for details
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
Credits
Built with:
- FastMCP - Python framework for MCP servers
- Model Context Protocol - Open protocol for AI-application integration
- Examplary API - Exam management platform
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.