How to Use the JSON-LD SEO Compiler MCP in AutoGen

Q: Can an AutoGen agent validate schemas using the JSON-LD SEO Compiler?

Yes. An agent can send raw property blocks to the buildschema tool, which returns a formatted script block. Another agent can then check this block for compliance.

Let your AutoGen agents debate, validate, and compile 100% compliant JSON-LD schemas without syntax errors.

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Setup JSON-LD SEO Compiler with AutoGen

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Multi-Agent Debate for Flawless Schemas

AutoGen shines when agents challenge each other. Have one agent draft the schema properties and another agent use the `build_schema` tool to compile them. A third agent can review the output against your SEO guidelines. This collaborative process catches missing required fields before deployment. If the writer agent forgets a product price, the reviewer flags it, and the compiler updates the schema until it's perfect.

Automate Schema Generation in AutoGen

Manual schema writing is tedious. With this MCP Server, your AutoGen agents can handle the entire workflow. The adapter handles schema conversion automatically, letting agents pass raw data directly to `build_schema`. The agents communicate in natural language, but they output precise code. You get a production-ready script tag that matches Google's specifications without writing a single line of manual validation logic.

Streamable HTTP Transport for AutoGen Agents

Large multi-agent systems need stable connections. This MCP Server supports Streamable HTTP transport, making it easy to connect your AutoGen system to the compiler tool even across distributed networks. Your agents can call `build_schema` from different environments without losing connection. It ensures fast, reliable compilation of structured data blocks during long-running multi-agent conversations.

Setup guide

Set up JSON-LD SEO Compiler MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes JSON-LD SEO Compiler tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="JSON-LD SEO Compiler_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent JSON-LD SEO Compiler data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="JSON-LD SEO Compiler_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent JSON-LD SEO Compiler data")
    print(result.messages[-1].content)

Get your connection token →

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Common questions about JSON-LD SEO Compiler MCP in AutoGen

Install the extension package, then use the AutoGen MCP server tools adapter with your HTTP URL. Pass the resulting tool list to your `AssistantAgent` constructor.

Yes. An agent can send raw property blocks to the `build_schema` tool, which returns a formatted script block. Another agent can then check this block for compliance.

LLMs often write invalid JSON-LD with incorrect syntax or hallucinated Schema.org types. The `build_schema` tool forces strict compliance, saving you from silent search engine penalties.

Yes. The AutoGen MCP adapter automatically maps the input schemas. Your agents can interact with the tool naturally without you writing custom parser code.

The MCP Server processes your schema keys and values in an ephemeral V8 sandbox. No data is stored, ensuring your proprietary business metadata remains private and secure.

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