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How to give an AI agent a country-aware document generator tool with Yowes

Connect the Yowes MCP server to an agent that lists countries and schools before generating samples.

Reverse engineering. An agent can generate many realistic credential-style files on its own, so limit its scope to a test folder and require a human review step before any file leaves the environment.

Who it is forAn agent builder who wants an agent to request synthetic education documents by country through a standard MCP connection.

The problemAgents need a callable tool with discoverable options, and building one for thirteen countries from scratch is slow.

The outcomeAn MCP-connected agent that discovers countries and schools, then generates documents on request.

What you need first

  • Python 3.10 or newer
  • pip, or uv for the uvx route
  • An MCP client that speaks stdio, such as the clients named in the README
  • A test environment with synthetic data only

Steps

  1. Install the wheel with pip install dist/yowes_doc_generator-0.1.0-py3-none-any.whl or install from source with pip install -e .
  2. Run the server with uvx --from . yowes-mcp
  3. Register the stdio server in your agent runtime's MCP settings
  4. Let the agent call list_countries_tool and list_schools before any generation call
  5. Review each generated file in output/ before the agent passes it to any downstream step

Prompt for your agent

Connect to the yowes MCP server from the hirotomasato/yowes repo over stdio. Call list_countries_tool, then list_schools for <country code>, and report the country codes and school names found. Expected output: a list of valid options with no documents created until asked. Verify that every returned country code matches one of the 13 in the README table.

Caveat. The README names the tools list_countries_tool and list_schools but does not document the generation tool's parameters, so check the exposed tool schema before writing agent calls.

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