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5 months ago
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2 months ago
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Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"anudeep-codespace-educhain_mcp_server": {
"command": "uv",
"args": [
"run",
"mcp",
"dev",
"main.py"
],
"env": {
"GOOGLE_API_KEY": "YOUR_GOOGLE_API_KEY"
}
}
}
}You can run Educhain’s MCP Server locally to generate learning content such as MCQs, flashcards, and lesson plans by interfacing a client (like Claude Desktop) with a Python-based MCP backend. It runs alongside an LLM (Gemini) and exposes a debugging proxy for development and testing.
How to use
To use the Educhain MCP Server, start it in dev mode and connect a client that supports MCP endpoints. You will obtain a local proxy URL to access the server’s resources and tools, then use the client to request MCQs, flashcards, or lesson plans.
How to install
Prerequisites: Node.js LTS is required for debugging steps that involve the MCP tooling. Python 3.10 is recommended for running the MCP server. Use a package manager that you prefer for Python packages.
# 1) Install Python (ensure python3 and pip are available)
# 2) Install uv (universal) as the MCP runtime
pip install uv
# 3) Initialize an existing project (if needed)
uv init
# 4) Add required MCP packages for Educhain
uv add "educhain" "mcp[cli]"
# 5) Set your Google Gemini API key in the environment file
# Inside .env file
GOOGLE_API_KEY=YOUR_GOOGLE_API_KEY
# 6) Run the MCP server in development mode
uv run mcp dev main.py
Additional sections
Configuration notes: The server exposes a local HTTP proxy for debugging when started in dev mode. You will see a tokenized proxy URL like http://localhost:6274/?PROXY\_API\_TOKEN=<proxy token> which you paste into a browser to connect. The client can then interact with Educhain’s components.
Environment and logs: Logs are typically written to platform-specific locations. Check the following paths to review logs after launching the server:
- Windows: %APPDATA%\Claude\logs\mcp.log
- macOS: ~/Library/Logs/Claude/mcp.log
Notes and caveats:
- Node.js (LTS) is required for debugging flows.
- pyenv is not recommended for this workflow.
- The frontend client (Claude Desktop) can connect to the MCP server once it is registered in the client with the appropriate command and arguments.
Config example
{
"mcpServers": {
"Educhain - MCP server": {
"command": "uv",
"args": [
"run",
"mcp",
"dev",
"main.py"
],
"env": {
"GOOGLE_API_KEY": "YOUR_GOOGLE_API_KEY"
}
}
}
}
Available tools
generate_mcq
Generates multiple-choice questions based on a given topic or curriculum outline.
generate_flashcard
Creates flashcards for key concepts to aid quick review and spaced repetition.
generate_lessonplan
Produces structured lesson plans outlining objectives, activities, and assessments.