Grepsr MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Grepsr 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 Grepsr. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Grepsr?"
)
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 Grepsr MCP Server
Connect your Grepsr account to any AI agent and take full control of your managed web scraping operations. Use natural language to trigger on-demand crawls, monitor data delivery schedules, and retrieve structured datasets directly into your workflow.
LlamaIndex agents combine Grepsr tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Report Orchestration — List all your reports and crawlers and retrieve specific configuration details natively
- Live Data Retrieval — Query and resolve structured records from specific reports or run histories flawlessly
- On-Demand Crawling — Trigger manual crawl runs for any report to refresh your datasets synchronously
- Execution Monitoring — Track the status and record counts of crawl histories to audit data quality flawlessly
- Webhook Management — Setup and audit webhooks to notify your internal systems as soon as new data is ready natively
- Integration Visibility — List active data delivery integrations including S3, SFTP, and cloud storage providers synchronously
The Grepsr MCP Server exposes 12 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 Grepsr to LlamaIndex via MCP
Follow these steps to integrate the Grepsr 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 12 tools from Grepsr
Why Use LlamaIndex with the Grepsr MCP Server
LlamaIndex provides unique advantages when paired with Grepsr through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Grepsr tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Grepsr tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Grepsr, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Grepsr tools were called, what data was returned, and how it influenced the final answer
Grepsr + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Grepsr MCP Server delivers measurable value.
Hybrid search: combine Grepsr real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Grepsr 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 Grepsr for fresh data
Analytical workflows: chain Grepsr queries with LlamaIndex's data connectors to build multi-source analytical reports
Grepsr MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Grepsr to LlamaIndex via MCP:
create_webhook
Configure a new webhook URL for a report
get_latest_data
Retrieve the most recent scraped dataset for a report
get_me
Get details for the current Grepsr account
get_report_data
Query scraped records from a specific report
get_report_details
Get metadata and configuration for a specific report
get_report_history
Retrieve the execution history (runs) for a specific report
get_usage_stats
Check account API usage and request limits
list_integrations
List active data delivery integrations (e.g. S3, SFTP)
list_projects
List all scraping projects
list_reports
List all reports and crawlers in your Grepsr account
list_webhooks
List webhooks configured for a specific report
run_report
Trigger an on-demand crawl for a specific report
Example Prompts for Grepsr in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Grepsr immediately.
"List my web scraping reports in Grepsr"
"Trigger a manual crawl for report ID 104"
"Show me the 5 most recent records from the 'Real Estate Listings' report"
Troubleshooting Grepsr MCP Server with LlamaIndex
Common issues when connecting Grepsr to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGrepsr + LlamaIndex FAQ
Common questions about integrating Grepsr 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 Grepsr 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 Grepsr to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.