How do I find my Harness API Key?

Log in to Harness, go to **My Profile** (bottom left), and select **API Keys**. You can generate either a Personal API Key or use a Service Account Token from there.

Where can I find my Account ID and Org ID?

The Account ID is visible in your browser's URL when logged in (e.g., `account/XYZ123`). The Organization ID is typically found in the project settings or sidebar (default is often 'default').

Can I trigger a pipeline execution via this integration?

Yes! Use the `execute_pipeline` tool by providing the project ID and pipeline ID. Harness will initiate the workflow immediately.

Is the integration secure for managing secrets?

Absolutely. The integration only lists the metadata of your secrets (like names and identifiers) through your API key. Your credentials are encrypted and stored securely in the Vinkius Cloud.

Harness MCP Server for Pydantic AI 11 tools — connect in under 2 minutes

Name: Harness
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 11 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Harness through 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 Harness "
            "(11 tools)."
        ),
    )

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

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Harness MCP Server

Connect your Harness.io platform to any AI agent and take full control of your software delivery and CI/CD pipelines through natural conversation.

Pydantic AI validates every Harness tool response against typed schemas, catching data inconsistencies at build time. Connect 11 tools through 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

Pipeline Management — List, inspect, and trigger pipeline executions across your projects.
Execution Monitoring — Get real-time status updates and step details for active deployments.
Project Oversight — Browse your organizational structure and list projects within specific organizations.
Secrets & Infrastructure — Access lists of secrets, connectors, and environments to ensure your infrastructure is correctly configured.
Audit & Compliance — Retrieve platform audit logs to monitor changes and ensure security standards.
Service Insights — List microservices and environments defined in your DevOps ecosystem.

The Harness MCP Server exposes 11 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 Harness to Pydantic AI via MCP

Follow these steps to integrate the Harness 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 11 tools from Harness with type-safe schemas

Why Use Pydantic AI with the Harness MCP Server

Pydantic AI provides unique advantages when paired with Harness 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 Harness integration code

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

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

Harness + Pydantic AI Use Cases

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

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

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

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

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

Harness MCP Tools for Pydantic AI (11)

These 11 tools become available when you connect Harness to Pydantic AI via MCP:

execute_pipeline

Trigger the execution of a pipeline

get_audit_logs

Retrieve platform audit logs

get_execution_status

Get status and step details for a specific pipeline execution

get_pipeline

Get details and YAML for a specific pipeline

list_connectors

List infrastructure connectors (Git, Docker, K8s, etc.)

list_environments

List environments defined in a project

list_executions

List executions for a specific pipeline

list_pipelines

List pipelines within a specific project

list_projects

List all projects in the configured Harness organization

list_secrets

List secrets configured in a project

list_services

List services (microservices) defined in a project

Example Prompts for Harness in Pydantic AI

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

"List all pipelines in project 'E-commerce App'."

"Execute the 'Production Deploy' pipeline for project ID app_502."

"Show the status of the latest execution for pipeline deploy_v1."

Troubleshooting Harness MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Harness + Pydantic AI FAQ

Common questions about integrating Harness 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 Harness MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.