folk MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Create Contact, Get Contact Details, List Contact Notes, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add folk 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 App Connector for LlamaIndex
The folk app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 6 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 folk. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in folk?"
)
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 folk MCP Server
Connect your folk CRM account to any AI agent and simplify how you manage your professional relationships, coordinate contact groups, and track interactions through natural conversation.
LlamaIndex agents combine folk tool responses with indexed documents for comprehensive, grounded answers. Connect 6 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
- Contact Oversight — List all contacts and retrieve detailed profile metadata, including custom fields and status.
- Group Management — Coordinate your contact lists by querying and managing specific groups in your folk workspace.
- Interaction Tracking — Retrieve a complete history of emails, meetings, and calls for any contact to maintain context.
- Relationship CRM — Create new contact records and update profile data programmatically via AI.
- Notes & Insights — List and query all notes and comments associated with your contacts to capture important details.
- Operational Visibility — Verify account configurations and monitor your professional ecosystem directly from the agent.
The folk MCP Server exposes 6 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.
All 6 folk tools available for LlamaIndex
When LlamaIndex connects to folk through Vinkius, your AI agent gets direct access to every tool listed below — spanning contact-management, relationship-tracking, crm-automation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a new contact
Get details for a specific contact
List notes for a contact
Optionally filter by group ID. List folk contacts
List folk groups
List interactions for a contact
Connect folk to LlamaIndex via MCP
Follow these steps to wire folk into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the folk MCP Server
LlamaIndex provides unique advantages when paired with folk through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine folk tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain folk tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query folk, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what folk tools were called, what data was returned, and how it influenced the final answer
folk + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the folk MCP Server delivers measurable value.
Hybrid search: combine folk real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query folk 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 folk for fresh data
Analytical workflows: chain folk queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for folk in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with folk immediately.
"List all active contacts in my folk account."
"Show me the recent interactions for 'John Miller' (ID: 10293)."
"Add a new contact: 'Anna White' (anna@example.com)."
Troubleshooting folk MCP Server with LlamaIndex
Common issues when connecting folk to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpfolk + LlamaIndex FAQ
Common questions about integrating folk MCP Server with LlamaIndex.