Stigg MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Gql Get Customer, Gql Get Entitlements State, Gql Provision Customer, and more

Name: Stigg
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 Stigg as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The Stigg MCP Server for LlamaIndex is a standout in the Developer Tools category — giving your AI agent 12 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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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 Stigg. "
            "You have 12 tools available."
        ),
    )

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

asyncio.run(main())

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About Stigg MCP Server

Connect your Stigg account to any AI agent to take full control of your pricing and packaging workflows. Manage the entire customer lifecycle from provisioning to usage reporting through natural conversation.

LlamaIndex agents combine Stigg 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

Customer Lifecycle — Create, update, and retrieve customer profiles using REST or GraphQL tools.
Subscription Management — Provision new subscriptions, fetch active plan details, or cancel them when needed.
Usage Reporting — Report metered feature usage in real-time to ensure accurate billing and entitlement enforcement.
Hybrid API Access — Choose between REST and GraphQL actions for flexible integration with your billing data.

The Stigg MCP Server exposes 12 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 12 Stigg tools available for LlamaIndex

When LlamaIndex connects to Stigg through Vinkius, your AI agent gets direct access to every tool listed below — spanning billing, subscriptions, saas-pricing, 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.

gql

Gql get customer on Stigg

Get customer details via GraphQL

gql

Gql get entitlements state on Stigg

Get entitlements state via GraphQL

gql

Gql provision customer on Stigg

Provision a customer and optional subscription via GraphQL

gql

Gql provision subscription on Stigg

Provision a subscription via GraphQL

gql

Gql report usage on Stigg

Report usage via GraphQL

rest

Rest cancel subscription on Stigg

Cancel a subscription via REST API

rest

Rest create customer on Stigg

Create a new customer via REST API

rest

Rest create subscription on Stigg

Create a subscription via REST API

rest

Rest get customer on Stigg

Retrieve a customer via REST API

rest

Rest get subscription on Stigg

Retrieve a subscription via REST API

rest

Rest report usage on Stigg

Report usage for metered features via REST API

rest

Rest update customer on Stigg

Update a customer via REST API

Connect Stigg to LlamaIndex via MCP

Follow these steps to wire Stigg 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 12 tools from Stigg

Why Use LlamaIndex with the Stigg MCP Server

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

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

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

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

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

Stigg + LlamaIndex Use Cases

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

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

Data enrichment: query Stigg 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 Stigg for fresh data

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

Example Prompts for Stigg in LlamaIndex

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

"Create a customer with ID 'cust_123', name 'Alice', and email 'alice@example.com' using REST."

"Report 50 units of usage for feature 'api-calls' for customer 'cust_123'."

"Get the details for customer 'cust_123' using GraphQL."

Troubleshooting Stigg MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Stigg + LlamaIndex FAQ

Common questions about integrating Stigg 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 Stigg tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

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