How to Use the Celigo integrator.io MCP in LlamaIndex

Q: How does LlamaIndex work with the Celigo integrator.io tools?

You use the McpToolSpec after connecting a BasicMCPClient. This exposes the Celigo functions as tools for a LlamaIndex agent. The agent can then call tools like listintegrations to answer questions or index the results.

Turn Celigo integrator.io logs and configs into a searchable knowledge base for your LlamaIndex agent.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Celigo integrator.io MCP to LlamaIndex

Create your Vinkius account to connect Celigo integrator.io 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 Celigo integrator.io with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Index Your Integration History

This server exposes your Celigo integrator.io setup as a set of tools. LlamaIndex doesn't just call these tools; it can automatically index their output. Use `list_integration_errors` and `list_integration_flows` to build a vector index of your entire integration history. Now you can ask questions in natural language, like "Which flows failed last night?" LlamaIndex finds the relevant indexed data and uses it to give you a grounded answer, not a guess.

Build RAG Apps on Live Celigo Data

Go beyond static documents. With this MCP Server, your RAG application can query live data directly from Celigo. When a user asks about a connection, the agent can call `list_integration_connections` in real-time to get the current status. This means your agent's answers are always up-to-date. Combine the live output from Celigo tools with your internal documentation to create a powerful, accurate support bot or a query engine for your DevOps team.

Query Your MCP Server with LlamaIndex

The `McpToolSpec` makes it simple to get started. Once you connect your client, LlamaIndex treats each Celigo operation as a function it can call. Your agent can query for information or trigger actions. For example, your agent could decide to call `run_integration_flow` based on a user's request. LlamaIndex handles the tool calling, so you can focus on building the query engine and defining how the agent should interpret the results.

Setup guide

Set up Celigo integrator.io 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 Celigo integrator.io 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 Celigo integrator.io tools.",
)
response = await agent.run("List recent Celigo integrator.io 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 Celigo integrator.io. 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 Celigo integrator.io 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 Celigo integrator.io MCP in LlamaIndex

You use the `McpToolSpec` after connecting a `BasicMCPClient`. This exposes the Celigo functions as tools for a LlamaIndex agent. The agent can then call tools like `list_integrations` to answer questions or index the results.

Yes, that's a primary use case. You can configure LlamaIndex to periodically run `list_integration_errors` and add the results to a vector index. Then you can query that index to find patterns or diagnose recurring issues.

Build a DevOps assistant. It could combine your internal docs with live data from this MCP server. When you ask "Why did the user sync fail?", it could check your docs for known issues and simultaneously call `list_integration_errors` for recent logs.

It can do both. While LlamaIndex is great for querying, its agents can also execute tools that change state. You can allow your agent to use the `run_integration_flow` tool to trigger flows directly from a prompt.

The connection is scoped to Celigo integration metadata, like flow definitions and error messages. Vinkius secures the connection through a single token, and the server runs in a zero-trust, ephemeral environment. The actual data passing through your flows is not accessed.

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