Can my AI agent actually trigger test runs remotely?

Yes! You can ask your agent to list your available tests, pick an ID, and say 'Run this sequence'. Testim's dynamic runner architecture handles the load while your AI returns the execution ID for you to track.

How can it help me troubleshoot a failed test run?

Typically, you'd open the Testim dashboard, navigate to the specific test suite run, and read the logs. With this integration, you just instruct the agent to retrieve results for that specific Execution ID; it will summarize error strings immediately in markdown.

Can I merge test changes through the agent?

Absolutely. Because Testim supports branching, your agent can act as a command terminal. Ask to list branches, select a recently updated feature branch, and say 'Merge branch feature-login into master'.

Testim MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Testim
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Testim through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Testim "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Testim?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Testim MCP Server

Connect your Testim project to any AI agent and bring your automated end-to-end testing orchestration directly into your workflow via natural conversation.

Pydantic AI validates every Testim tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Automated AI Tests — Browse your entire test suite, retrieve detailed test steps, and manually trigger specific tests or entire scheduled plans
Suite & Label Runs — Execute dynamic batches by triggering runs associated with specific labels or grouped within precise test suites
Execution Diagnostics — Pull pass/fail statuses, trace errors, and review specific execution logs immediately after a deployment
Branch Management — Check parallel development efforts by listing, creating, and even merging automated test branches without opening the Testim GUI

The Testim MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Testim to Pydantic AI via MCP

Follow these steps to integrate the Testim MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from Testim with type-safe schemas

Why Use Pydantic AI with the Testim MCP Server

Pydantic AI provides unique advantages when paired with Testim through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Testim integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Testim connection logic from agent behavior for testable, maintainable code

Testim + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Testim MCP Server delivers measurable value.

Type-safe data pipelines: query Testim with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Testim tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Testim and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Testim responses and write comprehensive agent tests

Testim MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Testim to Pydantic AI via MCP:

create_project_branch

Creates a new test development branch

get_execution_results

Retrieves the status and results of a specific test execution

get_test_details

Retrieves full details for a specific Testim test

list_project_branches

Lists all parallel development branches in the project

list_tests

Lists all automated tests in the Testim project

merge_project_branch

Typically merges a feature branch into master. Merges test changes from one branch into another

run_specific_test

Optionally provide a branch name. Returns an execution ID. Triggers an immediate run for a specific test

run_test_plan

Triggers a run for a defined test plan

run_test_suite

Triggers a run for all tests in a specific suite

run_tests_by_label

Triggers a run for all tests matching a specific label

Example Prompts for Testim in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Testim immediately.

"List all branches available in my Testim project."

"Trigger a plan run for "Nightly-Regression"."

"Retrieve the execution diagnostic summary for ID EXC-999333."

Troubleshooting Testim MCP Server with Pydantic AI

Common issues when connecting Testim to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Testim + Pydantic AI FAQ

Common questions about integrating Testim MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your Testim MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.