How to Use the Exa AI MCP in LlamaIndex
Turn web search results into a searchable knowledge base for your LlamaIndex applications.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Exa AI MCP to LlamaIndex
Create your Vinkius account to connect Exa AI to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Index Exa AI results for semantic retrieval
Run a `search_with_contents` to grab data and pipe it straight into your vector store. Your index grows with live information from the web. This prevents the agent from hallucinating by grounding answers in the text retrieved via `extract_page_content`. It builds a bridge between your documents and the internet.
Deploy the Exa AI MCP Server as a tool spec
Use the tool spec to convert the 12 endpoints into native functions. This makes the Exa AI MCP Server a first-class citizen in your LlamaIndex agent. Call `to_tool_list_async` to load everything. You can then filter available tools to keep your agent focused on specific retrieval tasks like `search_by_category`.
Retrieve highlights with Exa AI and LlamaIndex
Use `get_query_highlights` to pull snippets that matter. These chunks are ready for immediate ingestion into your index. It saves you tokens by avoiding full-page dumps. Your index stays efficient because you only store the most relevant parts of the search results.
Set up Exa AI MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports. - 3
Convert to LlamaIndex tools
Call
mcp_tool_spec.to_tool_list_async()to convert all Exa AI MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
# Connect to the MCP
mcp_client = BasicMCPClient(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)
# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()
# Create and run the agent
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt="You have access to Exa AI tools.",
)
response = await agent.run("List recent Exa AI data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Exa AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Exa AI MCP in LlamaIndex
Use it with your favorite AI tools
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Start using the Exa AI MCP today
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