> ## Documentation Index
> Fetch the complete documentation index at: https://docs.learningcommons.org/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Get started with Knowledge Graph: use the REST API or MCP server, or download JSONL data files for local querying.

export const EarlyAccessCallout = ({children}) => <div className="eyebrow-callout not-prose rounded-xl border border-gray-200/80 p-5 dark:border-white/10" style={{
  marginBottom: "1rem",
  borderRadius: "4px"
}}>
    <div className="mb-3">
      <Badge color="green" size="md" icon="flask">
        Early access
      </Badge>
    </div>
    <div className="callout-body text-[15px] leading-relaxed text-gray-700 dark:text-gray-300">{children}</div>
    <style>{`.callout-body a { text-decoration: underline; text-decoration-color: #178251; }`}</style>
  </div>;

## Using Knowledge Graph

You can access Knowledge Graph data in several ways:

* [Local files](#local-files)
* [REST API](#rest-api)
* [MCP server](#mcp-server)
* [Claude connector](#claude-connector)

Each access method has their own unique [use cases and benefits](/knowledge-graph/understanding-knowledge-graph/introduction#how-to-access-knowledge-graph).

## Steps

<Tabs>
  <Tab title="Local files">
    Query the Knowledge Graph for the educational data you're interested in.

    <Steps>
      <Step title="Download the Knowledge Graph JSONL files">
        See [download options](/knowledge-graph/using-knowledge-graph/local-files#download-options).
      </Step>

      <Step title="Install jq">
        Install [`jq`](https://jqlang.github.io/jq/) ↗, a lightweight command-line JSON processor.
      </Step>

      <Step title="Query the JSONL files">
        Query your downloaded files for the data you're interested in.

        e.g., To get Common Core Math Standards, filter for nodes with a [`StandardsFrameworkItem`](/knowledge-graph/graph-reference/academic-standards#standardsframeworkitem) label, a `Multi-State` [jurisdiction](/knowledge-graph/graph-reference/value-and-format-standards#jurisdictionenum) (Common Core), and a `Mathematics` [academic subject](/knowledge-graph/graph-reference/value-and-format-standards#academicsubjectenum):

        ```shellscript theme={null}
        jq -c 'select((.labels | contains(["StandardsFrameworkItem"])) and .properties.jurisdiction == "Multi-State" and .properties.academicSubject == "Mathematics")' nodes.jsonl > common_core_math_standards.jsonl
        ```
      </Step>
    </Steps>
  </Tab>

  <Tab title="REST API">
    <EarlyAccessCallout>
      The API is in early access and is actively evolving. We will continue expanding it, and breaking changes may occur as we improve accuracy and reliability. Email [support@learningcommons.org](mailto:support@learningcommons.org) ↗ with your feedback or issues.
    </EarlyAccessCallout>

    Retrieve a list of [Academic Standards](/knowledge-graph/graph-reference/academic-standards) for Multi-State Mathematics.

    <Steps>
      <Step title="Generate your API key">
        Sign up for the [Learning Commons Platform](https://platform.learningcommons.org?utm_source=docs\&utm_medium=knowledge-graph) ↗ to generate an API key and get your base API URL.
      </Step>

      <Step title="Get a standards framework UUID">
        Send a request to the `GET /standards-frameworks` API endpoint to get the `caseIdentifierUUID` for Multi-State Mathematics.

        <CodeGroup>
          ```shell cURL theme={null}
          curl -X GET \
            -H "x-api-key: YOUR_API_KEY" \
            "https://api.learningcommons.org/knowledge-graph/v0/standards-frameworks?academicSubject=Mathematics&jurisdiction=Multi-State"
          ```

          ```python Python theme={null}
          import os
          import requests

          # Setup
          api_key = os.getenv("API_KEY")  # Your API key from Learning Commons Platform
          base_url = os.getenv("BASE_URL")  # Your base URL from Learning Commons Platform; follows https://api.learningcommons.org/knowledge-graph/v0 format

          headers = { "x-api-key": api_key }

          response = requests.get(
              f"{base_url}/standards-frameworks",
              headers=headers,
              params={
                  "academicSubject": "Mathematics",
                  "jurisdiction": "Multi-State"
              }
          )

          result = response.json()
          print(result)
          ```

          ```javascript JavaScript theme={null}
          const apiKey = process.env.API_KEY; // Your API key from Learning Commons Platform
          const baseUrl = process.env.BASE_URL; // Your base URL from Learning Commons Platform

          const response = await fetch(
            `${baseUrl}/standards-frameworks?academicSubject=Mathematics&jurisdiction=Multi-State`,
            {
              method: 'GET',
              headers: { 'x-api-key': apiKey }
            }
          );

          const data = await response.json();
          console.log(data);
          ```
        </CodeGroup>

        Copy the `caseIdentifierUUID` from the response to use in the next step.
      </Step>

      <Step title="Retrieve Academic Standards">
        Use the `caseIdentifierUUID` with the `GET /academic-standards` API endpoint to retrieve the individual standards for that framework.

        <CodeGroup>
          ```shell cURL theme={null}
          curl -X GET \
            -H "x-api-key: YOUR_API_KEY" \
            "https://api.learningcommons.org/knowledge-graph/v0/academic-standards?standardsFrameworkCaseIdentifierUUID=YOUR_UUID_FROM_STEP_1"
          ```

          ```python Python theme={null}
          import os
          import requests

          # Setup
          api_key = os.getenv("API_KEY")  # Your API key from Learning Commons Platform
          base_url = os.getenv("BASE_URL")  # Your base URL from Learning Commons Platform
          framework_uuid = "YOUR_UUID_FROM_STEP_1"  # Copy from Step 1 response

          # Make request
          headers = {
              "x-api-key": api_key
          }

          response = requests.get(
              f"{base_url}/academic-standards",
              headers=headers,
              params={
                  "standardsFrameworkCaseIdentifierUUID": framework_uuid
              }
          )

          result = response.json()
          print(result)
          ```

          ```javascript JavaScript theme={null}
          const apiKey = process.env.API_KEY; // Your API key from Learning Commons Platform
          const baseUrl = process.env.BASE_URL; // Your base URL from Learning Commons Platform
          const frameworkUuid = "YOUR_UUID_FROM_STEP_1"; // From Step 1 response

          const response = await fetch(
            `${baseUrl}/academic-standards?standardsFrameworkCaseIdentifierUUID=${frameworkUuid}`,
            {
              method: 'GET',
              headers: {
                'x-api-key': apiKey
              }
            }
          );

          const data = await response.json();
          console.log(data);
          ```
        </CodeGroup>

        ```json Response theme={null}
        {
          "data": [
            {
              "identifier": "e1755456-c533-5a84-891e-59725c0479e0",
              "caseIdentifierURI": "https://satchelcommons.com/ims/case/v1p0/CFItems/6b9bf846-d7cc-11e8-824f-0242ac160002",
              "caseIdentifierUUID": "6b9bf846-d7cc-11e8-824f-0242ac160002",
              "name": null,
              "statementCode": "3.NF.A.1",
              "description": "Understand a fraction $\\frac{1}{b}$ as the quantity formed by 1 part when a whole is partitioned into b equal parts; understand a fraction $\\frac{a}{b}$ as the quantity formed by a parts of size $\\frac{1}{b}$.",
              "statementType": "Standard",
              "normalizedStatementType": "Standard",
              "jurisdiction": "Multi-State",
              "academicSubject": "Mathematics",
              "gradeLevel": ["3"],
              "inLanguage": "en-US",
              "dateCreated": null,
              "dateModified": "2025-02-05",
              "notes": null,
              "author": "1EdTech",
              "provider": "Learning Commons",
              "license": "https://creativecommons.org/licenses/by/4.0/",
              "attributionStatement": "Knowledge Graph is provided by Learning Commons under the CC BY-4.0 license. Learning Commons received state standards and written permission under CC BY-4.0 from 1EdTech."
            }
          ],
          "pagination": {
            "limit": 1,
            "nextCursor": "eyJpZGVudGlmaWVyIjogImUxNzU1NDU2LWM1MzMtNWE4NC04OTFlLTU5NzI1YzA0NzllMCJ9",
            "hasMore": true
          }
        }
        ```
      </Step>
    </Steps>
  </Tab>

  <Tab title="MCP server">
    <EarlyAccessCallout>
      Early access features and functionality are actively evolving, and breaking changes may occur as we expand capabilities and improve accuracy and reliability. [support@learningcommons.org](mailto:support@learningcommons.org)  ↗ with your feedback or issues.
    </EarlyAccessCallout>

    Ask about [Academic Standards](/knowledge-graph/graph-reference/academic-standards), [Learning Components](/knowledge-graph/graph-reference/learning-components), or [Learning Progressions](/knowledge-graph/graph-reference/learning-progressions).

    <Steps>
      <Step title="Generate your API key">
        Sign up for the [Learning Commons Platform](https://platform.learningcommons.org?utm_source=docs\&utm_medium=knowledge-graph) ↗ to generate an API key.
      </Step>

      <Step title="Choose an AI client">
        Download an AI client that supports MCP (e.g., OpenAI with the Responses API).
      </Step>

      <Step title="Set up environment variables">
        ```txt .env theme={null}
        OPENAI_API_KEY=
        MCP_AUTH_KEY=
        MCP_SERVER_URL=https://kg.mcp.learningcommons.org/mcp
        ```
      </Step>

      <Step title="Connect to the MCP server">
        Make a request to the MCP server with your question – e.g., "What are the learning components for California standard 4.OA.A.3?"

        <CodeGroup>
          ```python Python theme={null}
          import os
          import requests
          from dotenv import load_dotenv

          load_dotenv()

          response = requests.post(
              "https://api.openai.com/v1/responses",
              headers={
                  "Content-Type": "application/json",
                  "Authorization": f"Bearer {os.getenv('OPENAI_API_KEY')}",
              },
              json={
                  "model": "gpt-4o",
                  "tools": [
                      {
                          "type": "mcp",
                          "server_label": "learning-commons-kg",
                          "server_url": os.getenv("MCP_SERVER_URL"),
                          "require_approval": "never",
                          "headers": {"x-api-key": os.getenv("MCP_AUTH_KEY")},
                      }
                  ],
                  "input": "What are the learning components for California standard 4.OA.A.3?",
              },
          )

          print(response.json())
          ```

          ```javascript JavaScript theme={null}
          import "dotenv/config";

          const response = await fetch("https://api.openai.com/v1/responses", {
            method: "POST",
            headers: {
              "Content-Type": "application/json",
              Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
            },
            body: JSON.stringify({
              model: "gpt-4o",
              tools: [
                {
                  type: "mcp",
                  server_label: "learning-commons-kg",
                  server_url: process.env.MCP_SERVER_URL,
                  require_approval: "never",
                  headers: {"x-api-key": process.env.MCP_AUTH_KEY},
                },
              ],
              input: "What are the learning components for California standard 4.OA.A.3?",
            }),
          });

          console.log(await response.json());
          ```
        </CodeGroup>

        <Note>
          If using an SDK, verify how to pass in the MCP authorization key for your
          client.
        </Note>
      </Step>

      <Step title="Review the response">
        Your AI client will call Knowledge Graph MCP tools to return structured results (e.g., standard statements, [Learning Components](/knowledge-graph/graph-reference/learning-components), etc.).

        Inspect `mcp_call` output entries for tool names, arguments, and results.
      </Step>
    </Steps>
  </Tab>

  <Tab title="Claude connector">
    Get authoritative [Academic Standards](/knowledge-graph/graph-reference/academic-standards) data when asking about a standard code.

    <Steps>
      <Step title="Get Claude">
        Sign up for a [Claude](https://claude.ai/) ↗ account.
      </Step>

      <Step title="Enable the Claude connector">
        Set up the [Knowledge Graph integration in Claude](https://claude.ai/directory/6e94f5fc-5dc8-4f0a-9fcf-741bcab4e034) ↗ from the Claude connector directory.

        <Frame>
          <img src="https://mintcdn.com/czi-60a2a443/mTb6qndt7zn7CM1c/images/kg/lc-kg-claude-connector.png?fit=max&auto=format&n=mTb6qndt7zn7CM1c&q=85&s=08d96faf44521f19ea5d2cb020749387" alt="Learning Commons Claude Connector" width="1920" height="1388" data-path="images/kg/lc-kg-claude-connector.png" />
        </Frame>
      </Step>

      <Step title="Ask about a standard">
        Mention the grade level, state, and/or standard code (e.g., `5.NBT.A.2` or `RL.4.1`) that you are interested in:

        * "I'm a teacher in Iowa. Generate three project ideas that address W\.3.4."
        * "I am a 4th-grade teacher in California. A student is struggling with 4.OA.A.3. Which prior standards should I focus on?"

        Claude will use Knowledge Graph tools to look up the official statement, break [Academic Standards](/knowledge-graph/graph-reference/academic-standards) into [Learning Components](/knowledge-graph/graph-reference/learning-components), and trace [Learning Progressions](/knowledge-graph/graph-reference/learning-progressions).
      </Step>
    </Steps>
  </Tab>
</Tabs>

## Next steps

<CardGroup cols={2}>
  <Card icon="graduation-cap" href="/api-reference/platform-api/overview" title="API Reference">
    Explore other API endpoints to access Knowledge Graph data.
  </Card>

  <Card icon="graduation-cap" href="/knowledge-graph/using-knowledge-graph/claude-connector" title="Claude connector">
    See more example prompts and how the connector works behind the scenes.
  </Card>

  <Card icon="graduation-cap" href="/knowledge-graph/graph-reference/academic-standards" title="Entity and relationship reference">
    Understand the data models that make up the Knowledge Graph.
  </Card>

  <Card icon="graduation-cap" href="/knowledge-graph/using-knowledge-graph/mcp-server" title="MCP server">
    See server URL, authentication, available tools, and full examples.
  </Card>

  <Card icon="graduation-cap" href="/knowledge-graph/getting-started/tutorials" title="Tutorials">
    Follow step-by-step guides to build with the Knowledge Graph.
  </Card>
</CardGroup>