Adjust MCP Server for LlamaIndex 3 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Adjust 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 Adjust. "
"You have 3 tools available."
),
)
response = await agent.run(
"What tools are available in Adjust?"
)
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 Adjust MCP Server
Connect your Adjust account to your AI agent to unlock professional mobile measurement and attribution insights. From auditing app settings to inspecting device attribution and monitoring key performance indicators (KPIs), your agent handles your mobile growth data through natural conversation.
LlamaIndex agents combine Adjust tool responses with indexed documents for comprehensive, grounded answers. Connect 3 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
- App Automation — Retrieve and audit technical settings for your mobile applications, including event tokens and partner parameters
- Device Inspection — Verify the attribution status of specific devices using their advertising IDs (ADID) for testing and support
- KPI Monitoring — Retrieve aggregated performance metrics like installs, clicks, and sessions to monitor app growth
- Event Tracking Audit — List active event tokens and verify that your in-app events are correctly configured
- Attribution Oversight — Quickly identify which networks and campaigns are driving the most high-value users directly from chat
The Adjust MCP Server exposes 3 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 Adjust to LlamaIndex via MCP
Follow these steps to integrate the Adjust 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 3 tools from Adjust
Why Use LlamaIndex with the Adjust MCP Server
LlamaIndex provides unique advantages when paired with Adjust through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Adjust tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Adjust tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Adjust, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Adjust tools were called, what data was returned, and how it influenced the final answer
Adjust + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Adjust MCP Server delivers measurable value.
Hybrid search: combine Adjust real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Adjust 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 Adjust for fresh data
Analytical workflows: chain Adjust queries with LlamaIndex's data connectors to build multi-source analytical reports
Adjust MCP Tools for LlamaIndex (3)
These 3 tools become available when you connect Adjust to LlamaIndex via MCP:
get_app_settings
Get app configuration
get_kpi_report
Filterable by date. Get aggregated KPI metrics
inspect_device
Inspect device attribution
Example Prompts for Adjust in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Adjust immediately.
"Retrieve the settings for my app with token 'abcdef123456'."
"Inspect the attribution status for ADID '12345-67890'."
"Show me the total installs for last week."
Troubleshooting Adjust MCP Server with LlamaIndex
Common issues when connecting Adjust to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAdjust + LlamaIndex FAQ
Common questions about integrating Adjust 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 Adjust 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 Adjust to LlamaIndex
Get your token, paste the configuration, and start using 3 tools in under 2 minutes. No API key management needed.