X (Twitter) 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 X (Twitter) as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 X (Twitter). "
"You have 3 tools available."
),
)
response = await agent.run(
"What tools are available in X (Twitter)?"
)
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 X (Twitter) MCP Server
Connect your X (Twitter) developer account to any AI agent and take full control of your social listening workflow through natural conversation.
LlamaIndex agents combine X (Twitter) tool responses with indexed documents for comprehensive, grounded answers. Connect 3 tools through the 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
- Recent Tweet Search — Search for latest public discussions (up to past 7 days) across the network using exact keywords, hashtags, or handles
- User Lookups — Fetch precise profile metadata of a specific user by their @username, revealing follower counts, verified states, and biographies
- Tweet Introspection — Provide a raw Tweet ID and instantly collect isolated text content alongside full engagement metrics (likes, retweets)
The X (Twitter) 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 X (Twitter) to LlamaIndex via MCP
Follow these steps to integrate the X (Twitter) 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 X (Twitter)
Why Use LlamaIndex with the X (Twitter) MCP Server
LlamaIndex provides unique advantages when paired with X (Twitter) through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine X (Twitter) tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain X (Twitter) tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query X (Twitter), a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what X (Twitter) tools were called, what data was returned, and how it influenced the final answer
X (Twitter) + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the X (Twitter) MCP Server delivers measurable value.
Hybrid search: combine X (Twitter) real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query X (Twitter) 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 X (Twitter) for fresh data
Analytical workflows: chain X (Twitter) queries with LlamaIndex's data connectors to build multi-source analytical reports
X (Twitter) MCP Tools for LlamaIndex (3)
These 3 tools become available when you connect X (Twitter) to LlamaIndex via MCP:
get_tweet_details
Retrieve the text and engagement metrics of a specific Tweet by its numeric ID
lookup_user_by_username
Do not include the "@" symbol. Fetch full details of a specific Twitter/X user by their @username (follower count, bio, verified status)
search_recent_tweets
Provide a search query string. Search for recent public tweets (up to last 7 days) using keywords, hashtags, or handles
Example Prompts for X (Twitter) in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with X (Twitter) immediately.
"Search for tweets mentioning 'Vinkius Cloud' over the last couple days."
"Look up the profile details for 'elonmusk'."
"Get the engagement stats for tweet ID 123456789."
Troubleshooting X (Twitter) MCP Server with LlamaIndex
Common issues when connecting X (Twitter) to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpX (Twitter) + LlamaIndex FAQ
Common questions about integrating X (Twitter) 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 X (Twitter) with your favorite client
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Connect X (Twitter) to LlamaIndex
Get your token, paste the configuration, and start using 3 tools in under 2 minutes. No API key management needed.