Exa 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 Exa 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 Exa. "
"You have 3 tools available."
),
)
response = await agent.run(
"What tools are available in Exa?"
)
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 Exa MCP Server
Connect your AI agent to Exa — the semantic search engine built from the ground up for AI applications.
LlamaIndex agents combine Exa 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
- Semantic Search — Search the web using natural language. Unlike Google, Exa understands concepts and meaning, returning results that are semantically relevant even without exact keyword matches
- Find Similar — Provide any URL and discover web pages with similar content. Perfect for competitive analysis, research expansion, and content discovery
- Extract Contents — Get clean text, highlights, and summaries from any list of URLs. Ideal for building knowledge bases from curated sources
The Exa 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 Exa to LlamaIndex via MCP
Follow these steps to integrate the Exa 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 Exa
Why Use LlamaIndex with the Exa MCP Server
LlamaIndex provides unique advantages when paired with Exa through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Exa tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Exa tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Exa, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Exa tools were called, what data was returned, and how it influenced the final answer
Exa + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Exa MCP Server delivers measurable value.
Hybrid search: combine Exa real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Exa 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 Exa for fresh data
Analytical workflows: chain Exa queries with LlamaIndex's data connectors to build multi-source analytical reports
Exa MCP Tools for LlamaIndex (3)
These 3 tools become available when you connect Exa to LlamaIndex via MCP:
exa_find_similar
Useful for finding competitors, related articles, or alternative sources on the same subject. Find web pages semantically similar to a given URL. Perfect for competitive analysis and content discovery
exa_get_contents
Useful when you already know which pages you want to read and need their content in a structured format. Extract clean text content from specific URLs. Provide comma-separated URLs to retrieve their content
exa_search
Returns page text, highlights, and relevance scores. Supports search types: auto (default), instant (fastest), fast, deep (most thorough). Search the web using Exa semantic search engine. Finds conceptually relevant results, not just keyword matches
Example Prompts for Exa in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Exa immediately.
"Search for companies building memory infrastructure for AI agents."
"Find pages similar to https://docs.langchain.com/docs/get_started/introduction"
"Extract the content from these 3 URLs: https://arxiv.org/abs/2401.00001, https://openai.com/blog, https://anthropic.com/research"
Troubleshooting Exa MCP Server with LlamaIndex
Common issues when connecting Exa to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpExa + LlamaIndex FAQ
Common questions about integrating Exa 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 Exa 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 Exa to LlamaIndex
Get your token, paste the configuration, and start using 3 tools in under 2 minutes. No API key management needed.