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 CrewAI 11 tools — connect in under 2 minutes

Name: Harness
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 11 Tools Framework

Connect your CrewAI agents to Harness through the Vinkius — pass the Edge URL in the `mcps` parameter and every Harness tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Harness Specialist",
    goal="Help users interact with Harness effectively",
    backstory=(
        "You are an expert at leveraging Harness tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Harness "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 11 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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.

When paired with CrewAI, Harness becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Harness tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Harness MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 11 tools from Harness

Why Use CrewAI with the Harness MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Harness through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Harness + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Harness for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Harness, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Harness tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Harness against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Harness MCP Tools for CrewAI (11)

These 11 tools become available when you connect Harness to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Harness + CrewAI FAQ

Common questions about integrating Harness MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.