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 LangChain 11 tools — connect in under 2 minutes

Name: Harness
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 11 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Harness through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "harness": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Harness, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

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.

LangChain's ecosystem of 500+ components combines seamlessly with Harness through native MCP adapters. Connect 11 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

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

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 11 tools from Harness via MCP

Why Use LangChain with the Harness MCP Server

LangChain provides unique advantages when paired with Harness through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Harness MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Harness queries for multi-turn workflows

Harness + LangChain Use Cases

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

RAG with live data: combine Harness tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Harness, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Harness tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Harness tool call, measure latency, and optimize your agent's performance

Harness MCP Tools for LangChain (11)

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

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

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Harness + LangChain FAQ

Common questions about integrating Harness MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.