Cody AI MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Cody AI 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 Cody AI. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Cody AI?"
)
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 Cody AI MCP Server
Connect your AI to Cody AI, the business AI assistant that can be trained on your own knowledge base.
LlamaIndex agents combine Cody AI tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Bot Management — List active bots, check their configurations, and view which documents they're trained on.
- Conversations — Start conversations with any bot and ask questions against your knowledge base.
- Document Import — Import web pages and files into specific folders to expand a bot's knowledge.
The Cody AI MCP Server exposes 10 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 Cody AI to LlamaIndex via MCP
Follow these steps to integrate the Cody AI 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 10 tools from Cody AI
Why Use LlamaIndex with the Cody AI MCP Server
LlamaIndex provides unique advantages when paired with Cody AI through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Cody AI tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Cody AI tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Cody AI, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Cody AI tools were called, what data was returned, and how it influenced the final answer
Cody AI + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Cody AI MCP Server delivers measurable value.
Hybrid search: combine Cody AI real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Cody AI 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 Cody AI for fresh data
Analytical workflows: chain Cody AI queries with LlamaIndex's data connectors to build multi-source analytical reports
Cody AI MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Cody AI to LlamaIndex via MCP:
create_conversation
Create a new conversation session with a specific bot
get_bot_details
Retrieve detailed information about a specific bot
get_document_status
Check the syncing status of a document to see if the AI has finished learning it
import_webpage
Import content from a URL into a specific folder in your knowledge base
list_bots
Retrieve all bots configured in your Cody AI account
list_conversations
Retrieve a list of recent conversations
list_documents
Retrieve a list of documents in your knowledge base
list_folders
Retrieve a list of folders in your knowledge base
list_messages
Retrieve the message history for a specific conversation
send_message
Send a prompt to the AI in a specific conversation
Example Prompts for Cody AI in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Cody AI immediately.
"Show me all active bots in Cody AI."
"Ask bot 'bot-xxxx': 'How do I reset my password?'"
"Import my local 'compliance_guidelines.pdf' into the Legal Bot's knowledge base."
Troubleshooting Cody AI MCP Server with LlamaIndex
Common issues when connecting Cody AI to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCody AI + LlamaIndex FAQ
Common questions about integrating Cody AI 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 Cody AI 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 Cody AI to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.