MCP server

Use the MCP server to access knowledge graph our data.

The Knowledge Graph MCP Server implements the Model Context Protocol ↗ for K-12 educational data.

Instead of relying on model recall, the MCP Server relies on tools ↗ and structured Knowledge Graph data to:

• Resolve Academic Standards
• Deconstruct them into granular Learning Components
• Trace Learning Progressions across standards

What you’ll need

• MCP Server URL:

  https://kg.mcp.learningcommons.org/mcp
  

• API keys generated in the Learning Commons Platform ↗ to include in your request headers for authentication:

  x-api-key: YOUR_API_KEY
  

  or

  Authorization: Bearer YOUR_API_KEY
  
  If using an SDK, verify how to pass in the MCP authorization key for your client.

Steps

1. Set up environment variables

   .env

   OPENAI_API_KEY=sk-...
   MCP_AUTH_KEY=your_learning_commons_api_key
   MCP_SERVER_URL=https://kg.mcp.learningcommons.org/mcp
   
2. Connect to the MCP server

   Make a request to the MCP server with your question — for example, asking about skills and unfinished learning for California standard 4.OA.A.3:

   Python

   import os
   import requests
   from dotenv import load_dotenv
   
   load_dotenv()
   
   openai_api_key = os.getenv("OPENAI_API_KEY")
   mcp_server_url = os.getenv("MCP_SERVER_URL")
   mcp_auth_key   = os.getenv("MCP_AUTH_KEY")
   
   input_prompt = "I am a 4th grade teacher in California. A new student in my class is struggling with the concepts related to 4.OA.A.3. What are the skills required for mastery and what potential unfinished learning should I address?."
   
   response = requests.post(
     "https://api.openai.com/v1/responses",
     headers={
       "Content-Type":  "application/json",
       "Authorization": f"Bearer {openai_api_key}",
     },
     json={
       "model": "gpt-4o",
       "tools": [
         {
           "type": "mcp",
           "server_label": "learning-commons-kg",
           "server_url": mcp_server_url,
           "require_approval": "never",
           "headers": { "x-api-key": mcp_auth_key }
         }
       ],
       "input": input_prompt
     }
   )
   
   print(response.status_code)
   for item in response.json()["output"]:
     if item["type"] == "mcp_call":
       print(f"Tool called: {item['name']}")
       print(f"Arguments:   {item['arguments']}")
       print(f"Result:      {item['output']}")
     elif item["type"] == "message":
       print(f"Answer: {item['content'][0]['text']}")
   
3. Review the response

   Your AI client will call Knowledge Graph MCP tools to return structured results (e.g., Academic Standard statements, Learning Components, or Learning Progressions).

   Inspect mcp_call output entries for tool names, arguments, and results.

Tools

Please review the Knowledge Graph License before using these tools.

The MCP server contains the following tools ↗, which can be used individually or in sequence:

Tool	Description
Find Academic Standard statement	Resolves an education standard code into its authoritative statement and metadata, optionally scoped to a jurisdiction
Find Learning Components from standard	Breaks a broad standard down into granular Learning Components that represent individual teachable skills
Find Learning Progressions from standard	Identifies prior or subsequent standards in a learning progression, based on the Student Achievement Partners (SAP) Coherence Map for Mathematics

A common workflow may use all 3 tools:

• Resolving a standard code to its official statement
• Retrieving the associated learning components for targeted instruction
• Tracing progressions to identify prior or follow-on standards

Inputs

Tool	Field	Type	Required	Description
Find Academic Standard statement	statementCode	string	✓	e.g., RI.5.2 or 8.F.B.4
	jurisdiction	string		Jurisdiction where standard is adopted (e.g., Maryland)
Find Learning Components from standard	caseIdentifierUUID	string	✓	UUID of the standard in the CASE Network
Find Learning Progressions from standard	caseIdentifierUUID	string	✓	UUID of the standard in the CASE Network
	direction	string	✓	backward for prerequisites and forward for subsequent