How do I find my Harvest Access Token and Account ID?

Go to the **Harvest Developers** site (id.getharvest.com), navigate to **Personal Access Tokens**, and create a new token. You will find both the **token** and the **Account ID** listed there.

Can I see time entries for a specific period?

Yes! Use the `list_time_entries` tool and provide the `from` and `to` dates in YYYY-MM-DD format to retrieve records for that timeframe.

Is it possible to create invoices through this integration?

Yes, you can use the `create_invoice` tool by providing a `client_id` and an optional `subject` to generate a new invoice draft in your Harvest account.

Is the integration secure for managing financial data?

Absolutely. The integration uses official Harvest API tokens over HTTPS. Your credentials are encrypted and stored securely within the Vinkius Cloud infrastructure.

Harvest MCP Server for LlamaIndex 11 tools — connect in under 2 minutes

Name: Harvest
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 11 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Harvest 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 Harvest. "
            "You have 11 tools available."
        ),
    )

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

asyncio.run(main())

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About Harvest MCP Server

Connect your Harvest account to any AI agent and take full control of your time tracking, client management, and invoicing through natural conversation.

LlamaIndex agents combine Harvest tool responses with indexed documents for comprehensive, grounded answers. Connect 11 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

Time Tracking Oversight — List and inspect tracked time entries to monitor team productivity.
Client Management — List all clients, create new ones, and update company details effortlessly.
Invoicing Automation — Access your invoice history, create new drafts, and manage billing statuses.
Project Monitoring — List all active projects and retrieve detailed information for each.
User Profile — Get information about the current authenticated user and account status.
Operational Efficiency — Use AI to identify unbilled time or upcoming invoice deadlines across your organization.

The Harvest MCP Server exposes 11 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 Harvest to LlamaIndex via MCP

Follow these steps to integrate the Harvest 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 11 tools from Harvest

Why Use LlamaIndex with the Harvest MCP Server

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

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

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

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

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

Harvest + LlamaIndex Use Cases

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

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

Data enrichment: query Harvest 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 Harvest for fresh data

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

Harvest MCP Tools for LlamaIndex (11)

These 11 tools become available when you connect Harvest to LlamaIndex via MCP:

create_client

Create a new client in Harvest

create_invoice

Create a new invoice for a client

delete_client

Permanently delete a client

get_client

Get detailed information for a specific client

get_invoice

Get details for a specific invoice

get_my_profile

Get information about the current authenticated user

list_clients

List all clients in your Harvest account

list_invoices

List all invoices, including drafts and sent ones

list_projects

List all projects in the account

list_time_entries

List tracked time entries

update_client

Update an existing client name

Example Prompts for Harvest in LlamaIndex

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

"List all time entries from last week."

"Create a new client named 'Acme Corp'."

"Show me all active projects."

Troubleshooting Harvest MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Harvest + LlamaIndex FAQ

Common questions about integrating Harvest 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 Harvest tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.