How to Use the Assertible MCP in Pydantic AI

Q: How do I run all Assertible tests using Pydantic AI?

Register the MCP toolset and call runservicetests with your service ID. The response is validated against strict Pydantic models.

Q: Can Pydantic AI fetch Assertible status badges?

Use getservicestatusbadge or getteststatusbadge to retrieve markdown status badges. The agent receives structured strings that fit your models.

Q: How do I update Assertible API specs from Pydantic AI?

Call syncspecification with your sync token. This uploads your OpenAPI or Swagger schemas directly from your Pydantic AI runtime.

Q: Is my Assertible API token secure with this setup?

Yes. Your ASSERTIBLESYNCTOKEN and deployment metadata are stored securely in your environment variables, passing through an ephemeral, zero-trust MCP environment.

Trigger type-safe Assertible testing workflows directly from your Pydantic AI agents.

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Connect Assertible MCP to Pydantic AI

Create your Vinkius account to connect Assertible to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Assertible with Pydantic AI

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Type-Safe Deployment Triggers

`create_deployment` registers a new deployment in Assertible and runs your automated API tests while Pydantic AI validates the response structure at runtime. This keeps your deploy pipeline reliable. If the returned Assertible deployment data doesn't match your Pydantic AI schema, the framework fails immediately. This prevents your agent from making decisions based on corrupted state.

Validate API Payloads with Pydantic AI

`validate_json` executes Draft 4 JSON schema checks on your raw API payloads inside your Pydantic AI workflow. It runs locally with zero authentication requirements, ensuring fast execution. This MCP Server verifies incoming Assertible payloads before your Pydantic AI agent processes them. It blocks malformed JSON from entering your system.

Automated Spec Synchronization

`sync_specification` pushes your OpenAPI schemas to Assertible using your sync token directly from Pydantic AI. Your agent triggers this whenever a build finishes. This ensures your Assertible testing environment stays in sync with your local code changes. The Pydantic AI agent manages the synchronization process without manual intervention.

Setup guide

Set up Assertible MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "assertible-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Assertible tools.",
)

result = await agent.run("List recent Assertible transactions")
print(result.output)

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Common questions about Assertible MCP in Pydantic AI

Register the MCP toolset and call `run_service_tests` with your service ID. The response is validated against strict Pydantic models.

Use `get_service_status_badge` or `get_test_status_badge` to retrieve markdown status badges. The agent receives structured strings that fit your models.

Call `sync_specification` with your sync token. This uploads your OpenAPI or Swagger schemas directly from your Pydantic AI runtime.

The agent throws a validation error immediately. This stops the workflow before any corrupted data can propagate.

Yes. Your ASSERTIBLE_SYNC_TOKEN and deployment metadata are stored securely in your environment variables, passing through an ephemeral, zero-trust MCP environment.

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