How to Run an AI GraphQL Agent with OE Runtime

Query any GraphQL API with natural language. OE Runtime introspects your schema, constructs type-safe queries with variables, executes them against your API, and returns structured results — no GraphQL expertise required.

The Agent YAML

Create a file called agent.yaml inside a graphql/ directory:

name: GraphQL Agent
description: Run GraphQL queries and mutations
instructions: |
  You are a GraphQL API agent. Run queries to fetch data and mutations to create or update records.
  Always use variables for dynamic values — never interpolate directly into queries.
  Complete all steps fully before writing your report.
steps:
  - name: Introspect Schema
    content: |
      Call the GraphQL introspection query to understand the available types, queries, and mutations.
      List the key types and operations available.
  - name: Execute Operation
    content: |
      Based on the schema, run a sample query to fetch a list of records from the most relevant type.
      Use variables for any dynamic values. Return the raw result.
  - name: Report
    content: |
      Summarize what was returned:
      - Operation executed (query or mutation)
      - Fields fetched
      - Number of records returned
      - Key values from the first 3 records
connectors:
  - connection_name: My GraphQL API
    connection_type: graphql

The Config File

Create oe-config.json in the same directory:

{
  "llm": {
    "provider": "openai",
    "model": "gpt-4o",
    "apiKey": "YOUR_OPENAI_API_KEY"
  },
  "server": {
    "enabled": false,
    "port": 3333,
    "apiKey": "your-secret-api-key"
  },
  "connectors": [
    {
      "connection_name": "My GraphQL API",
      "connection_type": "graphql",
      "endpoint": "https://api.example.com/graphql",
      "headers": {
        "Authorization": "Bearer YOUR_TOKEN"
      }
    }
  ]
}

Replace the endpoint with your GraphQL API URL and set the Authorization header with your API token. The agent works with any GraphQL API including GitHub, Shopify, Hasura, and custom APIs.

Download OE Runtime

Run the Agent

Windows

oe-runtime-win.exe graphql/agent.yaml --config graphql/oe-config.json

macOS

chmod +x oe-runtime-macos

oe-runtime-macos graphql/agent.yaml --config graphql/oe-config.json

Linux

chmod +x oe-runtime-linux

oe-runtime-linux graphql/agent.yaml --config graphql/oe-config.json

Running as an API Server

Add --serve to start OE Runtime as an HTTP server on port 3333:

oe-runtime-win.exe --serve --config graphql/oe-config.json

Then send a request:

curl -X POST http://localhost:3333/run \
  -H "Content-Type: application/json" \
  -d '{"yaml": "graphql/agent.yaml", "params": {}}'

Or import the Postman collection (download above) to test all endpoints visually.

Use Cases

• API exploration and documentation — Point the agent at any GraphQL API to automatically introspect its full schema and produce a human-readable summary of available types, queries, and mutations. This is particularly useful when onboarding to a new API or auditing what a third-party service exposes.
• E-commerce data retrieval — Query a Shopify or WooCommerce GraphQL API to fetch product listings, order statuses, inventory levels, and customer data without writing custom integration code. The agent handles schema introspection and query construction automatically.
• CMS content fetching — Pull content from a headless CMS like Contentful, Sanity, or Strapi via their GraphQL API to generate reports or feed data into downstream workflows. The agent can extract structured content fields and format them for whatever output format you need.
• GitHub repository analysis — Use the GitHub GraphQL API to query repository stats, pull request details, issue lists, and contributor activity in a single structured request. GraphQL allows fetching exactly the fields needed, making it far more efficient than the REST API for complex data shapes.
• Hasura database queries — Query a Hasura-powered database using natural language and let the agent translate it into the correct GraphQL query with the right filters, sorting, and pagination. This gives non-technical teams access to database data without SQL knowledge.
• Data federation across services — Use a GraphQL federation gateway to query data from multiple microservices in a single request. The agent handles the complexity of the federated schema and returns a unified response from what would otherwise require multiple separate API calls.
• Mutation testing and verification — Run create, update, or delete mutations against a staging or development GraphQL API to verify that data is being written correctly. The agent checks the mutation response and confirms that the expected changes are reflected in a subsequent query.
• Automated reporting from internal APIs — Schedule the agent to query your internal GraphQL API daily and produce business metric reports from the latest data. No need to build a separate reporting layer — the agent reads from the same API your product uses and formats the output for stakeholders.