Stirling PDF MCP Server for LlamaIndexGive LlamaIndex instant access to 11 tools to Add Watermark, Cert Sign, Get All Requests, and more

Name: Stirling PDF
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Stirling PDF 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 for LlamaIndex

Open in ChatGPT Open in Claude Open in Perplexity

The Stirling PDF MCP Server for LlamaIndex is a standout in the Productivity category — giving your AI agent 11 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

python

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 Stirling PDF. "
            "You have 11 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Stirling PDF?"
    )
    print(response)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Stirling PDF MCP Server

Connect your Stirling PDF instance to any AI agent and take full control of your document workflows through natural conversation. This server allows you to process PDF files, convert formats, and monitor your self-hosted infrastructure.

LlamaIndex agents combine Stirling PDF tool responses with indexed documents for comprehensive, grounded answers. Connect 11 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

Document Manipulation — Add text watermarks with custom opacity and font sizes, or convert images directly into PDF documents.
Digital Security — Sign PDF documents using certificates with specific reasons and location metadata.
Server Monitoring — Track application status, version info, and detailed request metrics (POST/GET) across all endpoints.
Advanced Operations — Use the generic tool runner to access specialized features like merging, splitting, or extracting images from PDFs.
Enterprise Metrics — Access Prometheus metrics for deep observability into your document processing pipeline.

The Stirling PDF MCP Server exposes 11 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 11 Stirling PDF tools available for LlamaIndex

When LlamaIndex connects to Stirling PDF through Vinkius, your AI agent gets direct access to every tool listed below — spanning pdf-tools, watermarking, pdf-conversion, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

add

Add watermark on Stirling PDF

Add a watermark to a PDF document

cert

Cert sign on Stirling PDF

Sign a PDF document with a certificate

get

Get all requests on Stirling PDF

Get POST requests count for all endpoints

get

Get all unique requests on Stirling PDF

Get unique users count for all endpoints

get

Get load on Stirling PDF

Get total count of GET requests

get

Get prometheus metrics on Stirling PDF

Get Prometheus metrics (requires Enterprise tier)

get

Get requests on Stirling PDF

Get total count of POST requests

get

Get status on Stirling PDF

Get application status and version information

get

Get unique requests on Stirling PDF

Get count of unique users for POST requests

img

Img to pdf on Stirling PDF

Convert an image to a PDF document

run

Run generic tool on Stirling PDF

Pass additional parameters as a JSON string. Run any Stirling PDF tool by its ID

Connect Stirling PDF to LlamaIndex via MCP

Follow these steps to wire Stirling PDF into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 11 tools from Stirling PDF

Why Use LlamaIndex with the Stirling PDF MCP Server

LlamaIndex provides unique advantages when paired with Stirling PDF through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Stirling PDF tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Stirling PDF tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Stirling PDF, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Stirling PDF tools were called, what data was returned, and how it influenced the final answer

Stirling PDF + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Stirling PDF MCP Server delivers measurable value.

Hybrid search: combine Stirling PDF real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Stirling PDF 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 Stirling PDF for fresh data

Analytical workflows: chain Stirling PDF queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Stirling PDF in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Stirling PDF immediately.

"Check the current status and version of my Stirling PDF server."

"Add a 'CONFIDENTIAL' watermark to this PDF with 0.5 opacity."

"Convert this image to a PDF document named 'report.pdf'."

Troubleshooting Stirling PDF MCP Server with LlamaIndex

Common issues when connecting Stirling PDF to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Stirling PDF + LlamaIndex FAQ

Common questions about integrating Stirling PDF MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Stirling PDF tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.