How do I find my Workspace and Model IDs?

You can use the `list_workspaces` and `list_models` tools provided by this server. They will return a list of all accessible environments along with their unique IDs.

Are actions in Anaplan synchronous or asynchronous?

Most data actions (imports, exports, processes) are asynchronous. When you run them, they return a Task ID. You should then use `get_task_status` to monitor the progress until it reaches a 'COMPLETE' state.

Can I trigger an Anaplan process that contains multiple actions?

Yes, use the `run_process` tool. Processes in Anaplan are designed to run a sequence of imports, exports, and other actions in a specific order. You can monitor the entire process using the returned Task ID.

Anaplan MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: Anaplan
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Anaplan as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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 llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Anaplan. "
            "You have 10 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Anaplan?"
    )
    print(response)

asyncio.run(main())

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* 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 Anaplan MCP Server

Connect your Anaplan account to your AI agent to automate financial planning, supply chain, and sales operations. This MCP server allows you to discover workspaces and models, and trigger complex data integration tasks using natural language.

LlamaIndex agents combine Anaplan tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Workspace & Model Discovery — List all available workspaces and models to navigate your planning environment.
Execute Data Actions — Trigger and monitor imports, exports, and processes (groups of actions) to move data in and out of Anaplan.
Task Monitoring — Real-time tracking of asynchronous task statuses to ensure your data integrations complete successfully.
File Management — List files within your models to keep track of historical imports and exports.

The Anaplan MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex 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 Anaplan to LlamaIndex via MCP

Follow these steps to integrate the Anaplan MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

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 10 tools from Anaplan

Why Use LlamaIndex with the Anaplan MCP Server

LlamaIndex provides unique advantages when paired with Anaplan through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Anaplan tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Anaplan tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Anaplan, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Anaplan tools were called, what data was returned, and how it influenced the final answer

Anaplan + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Anaplan MCP Server delivers measurable value.

Hybrid search: combine Anaplan real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Anaplan to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Anaplan for fresh data

Analytical workflows: chain Anaplan queries with LlamaIndex's data connectors to build multi-source analytical reports

Anaplan MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Anaplan to LlamaIndex via MCP:

get_task_status

Get status of a running task

list_exports

List export actions for a model

list_files

List files in a model (exports/imports)

list_imports

List import actions for a model

list_models

List Anaplan models. Optionally filter by workspaceId

list_processes

List processes for a model

list_workspaces

List available Anaplan workspaces

run_export

Run an Anaplan export action

run_import

Run an Anaplan import action

run_process

Run an Anaplan process

Example Prompts for Anaplan in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Anaplan immediately.

"List all my Anaplan workspaces and models."

"Run the 'Monthly Actuals' import in the Finance workspace."

"What's the status of the process task 'p_456'?"

Troubleshooting Anaplan MCP Server with LlamaIndex

Common issues when connecting Anaplan to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Anaplan + LlamaIndex FAQ

Common questions about integrating Anaplan MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Anaplan tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.