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@synthbrew/agent lets MCP-capable agents create Synthbrew projects, validate schema configs, provision generated sources, create source API keys, and return runtime API docs.

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Install

Most MCP clients can launch the package directly with npx: 
npx -y @synthbrew/agent

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Environment variables

SYNTHBREW_API_KEY=sb_api_...
SYNTHBREW_API_URL=https://api.synthbrew.com/api
Use a team public API key from Settings > Team > Public API keys. Configure these in your MCP client. When run directly in a terminal, the process stays open and waits for MCP messages over stdio.

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MCP config

{
  "mcpServers": {
    "synthbrew": {
      "command": "npx",
      "args": ["-y", "@synthbrew/agent"],
      "env": {
        "SYNTHBREW_API_KEY": "sb_api_...",
        "SYNTHBREW_API_URL": "https://api.synthbrew.com/api"
      }
    }
  }
}
For client-specific setup, see: For local development, set SYNTHBREW_API_URL to your local API base: 
SYNTHBREW_API_URL=http://localhost:3311/api

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Agent workflow

The calling agent drafts the schema itself, then uses Synthbrew tools to validate and provision resources:
  1. Draft a canonical Synthbrew schemaVersionConfig using schemaConfigVersion: "v1" and formatVersion: 1.
  2. Call synthbrew_validate_schema_config.
  3. Fix validation errors and validate again.
  4. List or create a project.
  5. Create a schema.
  6. Create and populate a source.
  7. Create a source API key.
  8. Get runtime docs and return app integration examples.
  9. Fetch sample rows when the user wants to inspect generated data or needs realistic example payloads.
Source API keys beginning with sb_src_ are runtime secrets. Store them securely and do not commit them to source control.

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Schema config v1

The public agent contract is frozen as schemaConfigVersion: "v1". The schema config payload uses formatVersion: 1. Synthbrew may add optional fields, enum values, generation settings, and metadata fields to v1 without a new version. Synthbrew will not remove fields, rename fields, change existing meanings, or make optional fields required without introducing a new contract version. Validation requests can include the contract version explicitly: 
{
  "schemaConfigVersion": "v1",
  "schema": {
    "formatVersion": 1,
    "entities": []
  }
}

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Example prompts

Use prompts that describe the product or workflow you are building. The agent will turn the request into a Synthbrew schema, validate it, create the source, and return the details your app needs.

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Existing app schema

Point your coding agent at the schema files your app already uses when you want Synthbrew data that matches your local models: 
Use Synthbrew MCP to replicate my database schema at /db/models and generate 100,000 rows. Give me the source database credentials and runtime API docs afterward.
The agent can inspect the files, translate the models into a Synthbrew schema, validate the config, populate a source, and return the connection details. This is useful for local development, demos, QA, and frontend work where you need realistic sample rows without connecting to production-like customer data.

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SaaS analytics backend

Can you generate a Synthbrew schema for a B2B SaaS analytics app with accounts, users, subscriptions, invoices, product events, and support tickets? Generate 100,000 rows, keep the relationships realistic, create the data source, and give me the connection credentials and runtime API docs.
This should produce a relational dataset for dashboards such as MRR, churn, activation, event funnels, support volume, and account health.

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Marketplace demo data

Use Synthbrew to create a marketplace dataset with sellers, buyers, products, orders, order_items, payouts, reviews, and refunds. Generate enough data for a realistic admin dashboard, create the source, and return the API key plus example queries I can use in my app.
This gives frontend and analytics agents a full commerce workflow to build against without wiring a production database.

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CRM and sales pipeline

Create a Synthbrew schema for a sales CRM with companies, contacts, deals, activities, notes, tasks, and pipeline stages. Generate 50,000 realistic records across the tables, create a Postgres source, and return everything needed to connect my app to it.
This is useful when you want to build lead lists, kanban pipeline views, sales forecasts, activity timelines, and account detail pages.

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Available tools

  • synthbrew_validate_schema_config
  • synthbrew_list_projects
  • synthbrew_create_project
  • synthbrew_list_schemas
  • synthbrew_create_schema
  • synthbrew_list_schema_versions
  • synthbrew_list_sources
  • synthbrew_create_source
  • synthbrew_regenerate_source
  • synthbrew_get_generation_job
  • synthbrew_list_generation_events
  • synthbrew_list_source_api_keys
  • synthbrew_create_source_api_key
  • synthbrew_get_runtime_docs
  • synthbrew_get_source_sample_data
The package does not call Synthbrew’s AI schema generator. Your agent authors schemas and uses Synthbrew validation to repair them.