How to integrate Sap successfactors MCP with LlamaIndex

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Introduction

This guide walks you through connecting Sap successfactors to LlamaIndex using the Composio tool router. By the end, you'll have a working Sap successfactors agent that can show your current employee profile details, check your job title and department info, display your contact information in successfactors through natural language commands.

This guide will help you understand how to give your LlamaIndex agent real control over a Sap successfactors account through Composio's Sap successfactors MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Sap successfactors with

TL;DR

Here's what you'll learn:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Sap successfactors
  • Connect LlamaIndex to the Sap successfactors MCP server
  • Build a Sap successfactors-powered agent using LlamaIndex
  • Interact with Sap successfactors through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built for async/await patterns

What is the Sap successfactors MCP server, and what's possible with it?

The Sap successfactors MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Sap successfactors account. It provides structured and secure access to your HR data, so your agent can retrieve user information, access employee details, and drive workforce automation on your behalf.

  • Current user profile retrieval: Instantly fetch the authenticated user's profile and access up-to-date information about their SAP SuccessFactors account.
  • Employee data access: Allow your agent to securely obtain details about employees, enabling streamlined HR and workforce management workflows.
  • Personalized onboarding support: Use user data to personalize onboarding experiences, helping new hires get up to speed faster with relevant, contextual information.
  • Automated reporting: Enable your agent to pull user-related reports or summaries, supporting HR analytics and decision-making.
  • Seamless integration with enterprise HR processes: Connect user data to other HR tools or workflows, making it easier to automate tasks like leave approvals or performance tracking.

Supported Tools & Triggers

Tools
Approve Calibration SessionFinalize a calibration session that is in the In Progress or Approving status.
Create a Feedback RequestCreate a feedback request in SAP SuccessFactors Continuous Feedback.
Create Learning Activities BulkCreate learning activities and associate them with development goals in bulk (requires third-party LMS integration).
Create OnboardeeCreates a new onboardee in SAP SuccessFactors Onboarding 2.
Create or Update Successor NominationCreate or update a successor nomination for a position or talent pool in succession planning.
Delete NominationDelete a nomination for a position or talent pool in succession planning.
Get Application InterviewRetrieves interview information related to job applications from Interview Central.
Get Background EducationTool to retrieve background education records for employees from SAP SuccessFactors.
Get Background MobilityRetrieves mobility background records showing employee willingness to relocate.
Get Calibration Session By IDGet a specific calibration session by session ID.
Get Calibration SessionsQuery all the calibration sessions that a user can access.
Get Calibration Subject By IDQuery a specific subject's competency ratings and ratings within a calibration session.
Get Calibration Subject RatingsQuery a subject's ratings, competency ratings, and comments by using session ID.
Get CDP Learning MetadataGet metadata for Career Development Planning Learning service.
Get Current UserRetrieves the currently authenticated user's information from SAP SuccessFactors.
Get Custom MDF ObjectTool to retrieve custom MDF (Metadata Framework) objects from SAP SuccessFactors.
Get Employee Employment TerminationRetrieves employee termination information records from SAP SuccessFactors.
Get Employee TimeRetrieves employee time entries including time off records from SAP SuccessFactors.
Get Employee TimesheetRetrieves employee timesheet records for attendances, overtime, on-call times, and allowances.
Get Non-Recurring Pay ComponentsTool to retrieve non-recurring pay component information including bonuses and one-time payments from SAP SuccessFactors.
Get Recurring Pay ComponentsTool to retrieve recurring pay component information including salary and benefits data from SAP SuccessFactors.
Get Feedback RecordsTool to retrieve continuous feedback records from SAP SuccessFactors Performance and Goals module using OData V4 protocol.
Get FOBusinessUnitRetrieves foundation object business unit records for organizational structure hierarchy.
Get FOCompany RecordsRetrieves foundation object company records from SAP SuccessFactors.
Get Foundation Object Cost CentersRetrieves foundation object cost center records for organizational structure.
Get FODepartment RecordsTool to retrieve foundation object department records from SAP SuccessFactors.
Get Foundation Object Job CodesRetrieves foundation object job code records containing job classification information.
Get Job FunctionsTool to retrieve foundation object job function records for categorizing job roles.
Get Foundation Object LocationTool to retrieve foundation object location records for work locations.
Get FOPayGroupRetrieves foundation object pay group records for compensation and payroll groupings.
Get Form ContentRetrieves performance form content from SAP SuccessFactors.
Get Goal Plan TemplateRetrieves goal plan template information from SAP SuccessFactors.
Get Goals By PlanRetrieves performance goals data using the goal plan ID.
Get Interview Overall AssessmentTool to retrieve overall interview ratings and navigation for assessments from Interview Central.
Get Job ApplicationRetrieves job application records linking candidates to job requisitions.
Get Job Requisition Screening QuestionsTool to retrieve screening questions related to job requisitions from SAP SuccessFactors Recruiting.
Get Job RequisitionTool to retrieve job requisition records from SAP SuccessFactors Recruiting Management.
Get Calibration Session MetadataGet OData metadata for Calibration Session service.
Get Clock In/Out Integration MetadataGet OData metadata for Clock In/Clock Out Integration service.
Get Nomination Service MetadataGet OData metadata for Nomination service.
Get Onboarding Additional Services MetadataGet OData metadata for Onboarding Additional Services.
Get User Entity MetadataRetrieves the OData metadata document for the User entity describing its properties and operations.
Get Onboarding 2.0 ProcessesTool to retrieve Onboarding 2.
Get Pending Feedback RequestsTool to retrieve pending feedback requests or feedback request records from SAP SuccessFactors Continuous Feedback.
Get Personal Information RecordsTool to retrieve personal information records from SAP SuccessFactors Employee Central.
Get Person by IDTool to retrieve person information for an employee by their external person ID.
Get PicklistTool to retrieve picklist definitions from SAP SuccessFactors.
Get Picklist OptionRetrieves picklist option values with localized labels from SAP SuccessFactors.
Get PositionRetrieves position management records from SAP SuccessFactors Employee Central.
Get Talent PoolRetrieves talent pool records including members and nomination details.
Get Temporary Time InformationRetrieves temporary time information records from Time Management module.
Get Time Account SnapshotRetrieves time account snapshot data for leave liability calculation and payroll.
Get Work OrderTool to retrieve work order records for contingent worker management from SAP SuccessFactors.
Give Feedback or Respond to Feedback RequestTool to give performance feedback or respond to a feedback request in SAP SuccessFactors Continuous Performance Management.
List CandidatesTool to retrieve a list of candidates from SAP SuccessFactors.
List Employee Employment RecordsTool to retrieve a list of all employment records from SAP SuccessFactors.
List Person RecordsTool to retrieve a list of person records from SAP SuccessFactors Employee Central.
List UsersTool to retrieve a list of all employee users from SAP SuccessFactors.
Query All Available Clock In/Clock Out GroupsQuery all available clock in/clock out groups.
Query Clock In/Clock Out Group By CodeQuery a clock in/clock out group by code with time event types.
Refresh CDP Learning MetadataRefresh metadata for Career Development Planning Learning service.
Refresh Metadata for Continuous FeedbackRefresh metadata cache for Continuous Feedback service.
Update Calibration Subject RatingsUpdate a subject's competency ratings in a calibration session.
Update Username Post HiringUpdate the internal username of new hires after hiring process is completed from Active Directory.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Sap successfactors account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Sap successfactors

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID

Installing dependencies

pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv

Create a new Python project and install the necessary dependencies:

  • composio-llamaindex: Composio's LlamaIndex integration
  • llama-index: Core LlamaIndex framework
  • llama-index-llms-openai: OpenAI LLM integration
  • llama-index-tools-mcp: MCP client for LlamaIndex
  • python-dotenv: Environment variable management

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Sap successfactors access

Import modules

import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

Create a new file called sap successfactors_llamaindex_agent.py and import the required modules:

Key imports:

  • asyncio: For async/await support
  • Composio: Main client for Composio services
  • LlamaIndexProvider: Adapts Composio tools for LlamaIndex
  • ReActAgent: LlamaIndex's reasoning and action agent
  • BasicMCPClient: Connects to MCP endpoints
  • McpToolSpec: Converts MCP tools to LlamaIndex format

Load environment variables and initialize Composio

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["sap_successfactors"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Sap successfactors actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Sap successfactors actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, sap successfactors)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Sap successfactors tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

What's happening here:

  • We're creating a direct terminal interface to chat with your Sap successfactors database
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are displayed in a clear, readable format

Define the main entry point

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Sap successfactors

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Sap successfactors, then start asking questions.

Complete Code

Here's the complete code to get you started with Sap successfactors and LlamaIndex:

import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["sap_successfactors"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Sap successfactors actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Sap successfactors actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

Conclusion

You've successfully connected Sap successfactors to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Sap successfactors tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

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FAQ

What are the differences in Tool Router MCP and Sap successfactors MCP?

With a standalone Sap successfactors MCP server, the agents and LLMs can only access a fixed set of Sap successfactors tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Sap successfactors and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with LlamaIndex?

Yes, you can. LlamaIndex fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Sap successfactors tools.

Can I manage the permissions and scopes for Sap successfactors while using Tool Router?

Yes, absolutely. You can configure which Sap successfactors scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Sap successfactors data and credentials are handled as safely as possible.

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