How to Use the Sapling (Kallidus) MCP in CrewAI

Q: How do I connect the Sapling (Kallidus) MCP Server to CrewAI?

Pass your Vinkius URL directly into the mcps array when defining your agent. The framework automatically loads all the HR tools for that specific role.

Q: Can I restrict which Sapling (Kallidus) tools a CrewAI agent can use?

Use the MCPServerHTTP class and apply a toolfilter. This lets you give one agent access to onboarding tasks while restricting it from viewing compensation data through the MCP connection.

Deploy autonomous HR agents using CrewAI and the Sapling (Kallidus) MCP Server.

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MCP Servers — Included with Plan

Connect Sapling (Kallidus) MCP to CrewAI

Create your Vinkius account to connect Sapling (Kallidus) to CrewAI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Sapling (Kallidus) with CrewAI

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Autonomous HR Auditing

The `list_employees` tool provides the base roster for an auditing agent to check active personnel. A secondary agent then uses `get_employee` to pull the employment history and compensation details for every user on that list. These agents share memory during the session. The monitor agent watches the data collection while the analyzer flags any missing records or mismatched job titles.

Multi-Agent Onboarding Tracking

The `list_onboarding_tasks` tool feeds direct task updates to an IT provisioning agent. When a new hire finishes their HR paperwork, the agent catches the status change and alerts the equipment team. You run this process hierarchically. A manager agent delegates the specific checks to sub-agents, ensuring no step gets missed during the first week of employment.

Analyze Company Topology

The `list_groups`, `list_teams`, and `list_job_titles` tools expose the entire internal structure of the business. Your AI client maps these relationships to identify duplicate roles or empty departments. The crew operates entirely without human intervention. You set the initial research objective, and the agents query the MCP Server until they compile a complete organizational report.

Setup guide

Set up Sapling (Kallidus) MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Sapling (Kallidus) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Sapling (Kallidus) Analyst",
    goal="Access and analyze Sapling (Kallidus) data via MCP.",
    backstory="Expert analyst with direct Sapling (Kallidus) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Sapling (Kallidus) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Sapling (Kallidus) Analyst",
        goal="Access and analyze Sapling (Kallidus) data via MCP.",
        backstory="Expert analyst with direct Sapling (Kallidus) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Sapling (Kallidus) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Sapling. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Sapling (Kallidus) MCP in CrewAI

Pass your Vinkius URL directly into the `mcps` array when defining your agent. The framework automatically loads all the HR tools for that specific role.

Use the `MCPServerHTTP` class and apply a `tool_filter`. This lets you give one agent access to onboarding tasks while restricting it from viewing compensation data through the MCP connection.

Each agent maintains its own context but shares findings through the crew's memory. You only need one endpoint token for the entire team to operate.

The framework supports stdio, SSE, and Streamable HTTP. For hosted cloud deployments, Streamable HTTP provides the most stable connection to the HR system.

The tools extract raw compensation details and employment histories. Because the connection is ephemeral and handled via a V8 Isolate Sandbox, the financial data disappears the moment the agent finishes its task.

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