Can I update my knowledge base via the agent?

Yes! Use the `create_article` tool to add new information to your Ada knowledge base. This helps the AI bot stay up-to-date with your latest product or policy changes.

What are the API rate limits on Ada?

The default platform API limit is 10,000 requests per day (10 per second). Some specific endpoints, such as the Data Export API, have additional limits like 15,000 requests per day.

Are there quotas per knowledge article in Ada?

Yes, Knowledge Base APIs enforce a constraint of 100KB per individual article, up to a maximum limit of 50,000 global articles in your organization.

Ada MCP Server for LlamaIndex 4 tools — connect in under 2 minutes

Name: Ada
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 4 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Ada 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 Ada. "
            "You have 4 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Ada?"
    )
    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 Ada MCP Server

Connect your Ada account to your AI agent to unlock advanced customer service automation. From monitoring real-time conversations to managing your knowledge base and syncing user metadata, your agent handles conversational AI orchestration through natural language.

LlamaIndex agents combine Ada tool responses with indexed documents for comprehensive, grounded answers. Connect 4 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

Conversation Oversight — List and retrieve details of active or past support conversations to identify trends
End User Management — Manage user profiles and sync metadata (metavariables) between Ada and your external systems
Knowledge Management — Create, update, and list articles in your knowledge base to help your AI agent provide better answers
Real-time Analytics — Retrieve insights on automated resolution rates and agent handoff patterns
Compliance Support — Manage data privacy requests and conversation retention directly from your chat interface

The Ada MCP Server exposes 4 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 Ada to LlamaIndex via MCP

Follow these steps to integrate the Ada 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 4 tools from Ada

Why Use LlamaIndex with the Ada MCP Server

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

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

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

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

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

Ada + LlamaIndex Use Cases

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

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

Data enrichment: query Ada 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 Ada for fresh data

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

Ada MCP Tools for LlamaIndex (4)

These 4 tools become available when you connect Ada to LlamaIndex via MCP:

create_article

Needs title and text content. Add a new text article to the Ada knowledge base to immediately improve AI bot responses

get_end_user

Requires the End User ID. Retrieve profile information and custom metavariables for a specific Ada end user

list_articles

Retrieve the catalog of help articles used by the Ada AI agent to answer customer queries

list_conversations

Retrieve active and past customer support conversations handled by the Ada bot

Example Prompts for Ada in LlamaIndex

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

"Show me the last 5 conversations handled by Ada."

Troubleshooting Ada MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Ada + LlamaIndex FAQ

Common questions about integrating Ada 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.