Handwrytten MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Handwrytten as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Handwrytten. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Handwrytten?"
)
print(response)
asyncio.run(main())
* 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 Handwrytten MCP Server
Connect your Handwrytten account to any AI agent and take full control of your physical outreach and relationship management through natural conversation.
LlamaIndex agents combine Handwrytten 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
- Card Selection — Browse and list all available stationery and card categories for any occasion.
- Font Management — List and select from various realistic handwriting styles to personalize your notes.
- Order Automation — Send single or bulk handwritten cards with personalized messages directly from the chat.
- Address Book Access — Manage your saved recipients and retrieve address details for quick sending.
- Credit Monitoring — Instantly check your account credit balance to manage your outreach budget.
- Template Insights — Browse your message templates to maintain brand consistency in your physical mail.
The Handwrytten 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 Handwrytten to LlamaIndex via MCP
Follow these steps to integrate the Handwrytten 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 Handwrytten
Why Use LlamaIndex with the Handwrytten MCP Server
LlamaIndex provides unique advantages when paired with Handwrytten through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Handwrytten tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Handwrytten tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Handwrytten, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Handwrytten tools were called, what data was returned, and how it influenced the final answer
Handwrytten + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Handwrytten MCP Server delivers measurable value.
Hybrid search: combine Handwrytten real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Handwrytten 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 Handwrytten for fresh data
Analytical workflows: chain Handwrytten queries with LlamaIndex's data connectors to build multi-source analytical reports
Handwrytten MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Handwrytten to LlamaIndex via MCP:
get_credit_balance
Check current account credit balance
get_order
Get details for a specific order
list_address_book
List recipients in your address book
list_cards
List all available cards/stationery
list_categories
List all card categories
list_fonts
List all available handwriting fonts
list_gifts
List available gifts that can be included with cards
list_orders
List history of card orders
list_templates
List message templates
send_card
Requires card_id, font_id, message, and recipient details. Send a single handwritten card
Example Prompts for Handwrytten in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Handwrytten immediately.
"Send a 'Thank You' card to John Doe using font hwDavid."
"Check my current credit balance."
"List all available handwriting fonts."
Troubleshooting Handwrytten MCP Server with LlamaIndex
Common issues when connecting Handwrytten to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpHandwrytten + LlamaIndex FAQ
Common questions about integrating Handwrytten MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Handwrytten with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Handwrytten to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.