How to Use the Diffbot MCP in LlamaIndex

Q: Can LlamaIndex query the Diffbot Knowledge Graph dynamically?

Yes, your agent can call searchknowledgegraph as a query engine tool. LlamaIndex uses the tool's structured JSON response to synthesize answers for complex research prompts.

Q: Can I extract forum threads into my vector database?

Yes, you can run extractforumthread to isolate discussions and comments from noisy page layouts. This gives your search index clean conversational nodes instead of raw web markup.

Q: Is my proprietary company profile search data safe?

Vinkius routes all calls to enhancecompanyprofile through isolated, ephemeral sandboxes. Your search queries and enriched company profiles are instantly deleted from the server memory once the request completes.

Index structured web data from Diffbot directly into your LlamaIndex vector stores to eliminate RAG hallucinations.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Diffbot MCP to LlamaIndex

Create your Vinkius account to connect Diffbot 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.

GDPR Free for Subscribers

Setup Diffbot with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Build RAG Indexes with Diffbot Web Extraction

LlamaIndex can ingest clean, structured outputs from this MCP Server using `extract_article_data` instead of raw, noisy HTML. This means your vector embeddings represent actual content rather than navigation menus or footer links. You can feed product catalogs parsed by `extract_product_data` straight into your document store. Your retrieval-augmented generation pipeline gets highly accurate, structured data to query against.

Query the Knowledge Graph Using LlamaIndex

Your AI agent can search billions of entities by calling `search_knowledge_graph` during a query lifecycle. LlamaIndex treats the resulting corporate structures and funding data as a queryable index. This integration allows the agent to cross-reference local documents with real-time market data. You get answers grounded in Diffbot's massive database without manual web searches.

Semantically Search Structured Profiles

The `enhance_company_profile` tool fetches clean metadata that LlamaIndex converts into structured nodes. You can then run semantic searches over executive teams, industries, and technologies. Combining `enhance_person_profile` with your local vector store lets you build rich, queryable directories of industry leaders. The framework handles the indexing while this MCP Server handles the raw data extraction.

Setup guide

Set up Diffbot MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
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 provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to 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 Diffbot MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

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 Diffbot tools.",
)
response = await agent.run("List recent Diffbot data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Diffbot. 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.

Connect Diffbot now

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 Diffbot MCP in LlamaIndex

You use the McpToolSpec to load the MCP tools into your LlamaIndex environment. Once loaded, the outputs from `extract_article_data` can be converted directly into Document objects for indexing.

Yes, your agent can call `search_knowledge_graph` as a query engine tool. LlamaIndex uses the tool's structured JSON response to synthesize answers for complex research prompts.

The framework catches exceptions during tool execution, such as when `get_api_status` reports a connection issue. Your application can fall back to cached vector data instead of failing completely.

Yes, you can run `extract_forum_thread` to isolate discussions and comments from noisy page layouts. This gives your search index clean conversational nodes instead of raw web markup.

Vinkius routes all calls to `enhance_company_profile` through isolated, ephemeral sandboxes. Your search queries and enriched company profiles are instantly deleted from the server memory once the request completes.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript