How to Use the Concord (Workflow Orchestration) MCP in LlamaIndex

Q: Can I search Concord (Workflow Orchestration) logs using LlamaIndex?

Absolutely. You can fetch logs with getprocesslog, index them, and run semantic searches to find specific error patterns across your historical builds.

Turn Concord (Workflow Orchestration) data into searchable knowledge for your LlamaIndex RAG applications.

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Connect Concord (Workflow Orchestration) MCP to LlamaIndex

Create your Vinkius account to connect Concord (Workflow Orchestration) 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.

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Setup Concord (Workflow Orchestration) with LlamaIndex

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Index Concord workflows in LlamaIndex

Feed the output of `list_processes` and `list_organizations` directly into your vector store. Your index now understands your entire CI/CD footprint. When you ask questions about past builds, the agent retrieves grounded facts from the server. You stop hallucinating about build states and start querying reality.

Ground your LlamaIndex RAG on real API data

Use `get_project_details` to populate your knowledge base with live configuration data. This ensures your AI answers questions based on current project settings. Your RAG pipeline stays fresh because you can re-index whenever the underlying Concord state changes. It is the most accurate way to keep your documentation in sync with your code.

Automate discovery with LlamaIndex

The `list_repositories` tool allows your agent to crawl your project structure and map dependencies. Your AI builds a searchable catalog of your entire development ecosystem. Everything becomes discoverable through natural language queries. You find the right repository or project without digging through web interfaces.

Setup guide

Set up Concord (Workflow Orchestration) 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 Concord (Workflow Orchestration) 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 Concord (Workflow Orchestration) tools.",
)
response = await agent.run("List recent Concord (Workflow Orchestration) data")

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Common questions about Concord (Workflow Orchestration) MCP in LlamaIndex

LlamaIndex takes the JSON output from your server tools and converts it into nodes for your vector store. This turns raw CI/CD data into a queryable knowledge base.

Absolutely. You can fetch logs with `get_process_log`, index them, and run semantic searches to find specific error patterns across your historical builds.

It does. By using the McpToolSpec, you convert all 10 server tools into a format LlamaIndex uses for its FunctionAgent.

Your vector store resides where you host it. The MCP server only provides the data you request, and Vinkius ensures the transport is ephemeral.

Your Concord (Workflow Orchestration) instance manages authentication. The MCP server respects your existing permissions, ensuring the data LlamaIndex retrieves is authorized.

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