ValueSERP MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add ValueSERP 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 ValueSERP. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in ValueSERP?"
)
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 ValueSERP MCP Server
Connect your ValueSERP account to any AI agent and integrate highly scalable, reliable, and real-time Google search data parsing into your conversational flow, bypassing CAPTCHAs and blocks.
LlamaIndex agents combine ValueSERP tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Comprehensive Google Search — Perform rapid programmatic queries across Google Organic, Images, News, Videos, and Scholar straight from your agent's interface.
- E-Commerce & Local SEO — Access raw Google Places and Google Shopping data to analyze competitor margins, finding ratings, coordinates, and product price shifts.
- Intent Discovery — Retrieve predictive Google Autocomplete suggestions and 'People Also Ask' related snippets to understand semantic search behavior.
- Advanced SERP Queries — Execute highly customized parameter inputs targeting specific granular geolocation bounds (gl), language codes (hl), and synthetic device overrides.
The ValueSERP MCP Server exposes 10 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 ValueSERP to LlamaIndex via MCP
Follow these steps to integrate the ValueSERP 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 10 tools from ValueSERP
Why Use LlamaIndex with the ValueSERP MCP Server
LlamaIndex provides unique advantages when paired with ValueSERP through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine ValueSERP tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain ValueSERP tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query ValueSERP, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what ValueSERP tools were called, what data was returned, and how it influenced the final answer
ValueSERP + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the ValueSERP MCP Server delivers measurable value.
Hybrid search: combine ValueSERP real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query ValueSERP 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 ValueSERP for fresh data
Analytical workflows: chain ValueSERP queries with LlamaIndex's data connectors to build multi-source analytical reports
ValueSERP MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect ValueSERP to LlamaIndex via MCP:
custom_serp_search
Provide parameters as a JSON object. Executes a highly customized Google search with advanced parameters
get_related_questions
Retrieves "People Also Ask" questions and answers from Google
get_search_suggestions
Retrieves predictive search suggestions from Google autocomplete
google_image_search
Returns direct URLs to image files. Searches for images on Google
google_news_search
Searches for news articles on Google
google_places_search
Provide a place name and location. Searches for local businesses and places on Google Maps
google_scholar_search
Searches for academic publications and abstracts on Google Scholar
google_search
Provide a query string and optional location. Performs a standard Google search for organic results
google_shopping_search
Returns product names, prices, and merchant links. Searches for products and prices on Google Shopping
google_video_search
Searches for video content on Google
Example Prompts for ValueSERP in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with ValueSERP immediately.
"Search Google Scholar for recent papers on 'quantum computing error correction'."
"Find the top business ratings for 'pizza places in Chicago' using Google Places."
"Check Google Autocomplete suggestions when someone types 'how to start a'."
Troubleshooting ValueSERP MCP Server with LlamaIndex
Common issues when connecting ValueSERP to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpValueSERP + LlamaIndex FAQ
Common questions about integrating ValueSERP 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 ValueSERP 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 ValueSERP to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.