How to Use the AbstractAPI MCP in LlamaIndex
Index AbstractAPI enrichment data directly into your LlamaIndex vector stores to ground RAG applications with real-world context.
Works with every AI agent you already use
…and any MCP-compatible client
Connect AbstractAPI MCP to LlamaIndex
Create your Vinkius account to connect AbstractAPI 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.
Knowledge-augmented company profiles
The `enrich_company` tool fetches employee counts, industries, and LinkedIn links based on a domain name. LlamaIndex takes this raw output and indexes it into your vector store alongside your internal documents. Grounding your queries in live data prevents hallucinations. When a user asks about a specific vendor, your RAG application retrieves the exact API response rather than guessing the company details.
LlamaIndex MCP Server integration
The `website_screenshot` tool generates a permanent URL of a headless browser render. You can store these URLs in your index to maintain visual records of competitor landing pages over time. Fetching data via your MCP client requires minimal setup. You wrap the basic client in McpToolSpec and pass the resulting list to your FunctionAgent to handle the routing.
Semantic holiday and timezone search
The `list_holidays` tool returns arrays of public and national holidays for any ISO country code. Combining this with the `get_timezone` tool lets you build a searchable knowledge base of global operating hours. Agents can query past sessions to see when a specific market was closed. The framework treats the API output just like any other text chunk in your semantic search pipeline.
Set up AbstractAPI 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 AbstractAPI 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 AbstractAPI tools.",
)
response = await agent.run("List recent AbstractAPI data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AbstractAPI. 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
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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.
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Common questions about AbstractAPI MCP in LlamaIndex
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