Which Base URL should I use for my account?

If you are using the international version, use `https://api.coze.com`. For the Chinese version, use `https://api.coze.cn`.

Can I automatically list all published bots in a space?

Yes! Use the `list_bots` tool with your Space ID. Your agent will return a list of all bots that have been published and are ready for interaction.

How do I upload a new document to my knowledge base?

Use the `upload_document` tool with the target Dataset ID and the raw text content. Your agent will handle the ingestion process into the Coze RAG engine.

Coze MCP Server for LlamaIndex 11 tools — connect in under 2 minutes

Name: Coze
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 11 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Coze as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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 Coze. "
            "You have 11 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Coze?"
    )
    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 Coze MCP Server

Connect your AI agents to Coze (扣子), the advanced bot orchestration platform by ByteDance. This MCP provides 11 tools to manage the full lifecycle of your bots, from chat interactions to knowledge base document ingestion.

LlamaIndex agents combine Coze 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

Bot Interaction — Chat with published bots and handle multi-turn conversations with persistent history
Knowledge Engineering — Upload, list, and delete documents in knowledge base datasets for RAG optimization
Workspace Management — List available spaces and published bots to monitor your AI ecosystem
Action Handling — Submit tool outputs when bots require human-in-the-loop or external plugin results

The Coze MCP Server exposes 11 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 Coze to LlamaIndex via MCP

Follow these steps to integrate the Coze 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 11 tools from Coze

Why Use LlamaIndex with the Coze MCP Server

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

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

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

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

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

Coze + LlamaIndex Use Cases

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

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

Data enrichment: query Coze 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 Coze for fresh data

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

Coze MCP Tools for LlamaIndex (11)

These 11 tools become available when you connect Coze to LlamaIndex via MCP:

clear_conversation

Clear all messages from a conversation session

create_chat

Send a message to a Coze bot and get a response

delete_document

Delete documents from a dataset by ID

get_conversation_history

Retrieve the message list from a conversation

list_bots

List published bots in a specific Coze Space

list_datasets

List knowledge base datasets in a Coze Space

list_workspaces

List available Coze workspaces/spaces

publish_bot

Publish a Coze Bot draft

submit_tool_outputs

Submit outputs for tools/plugins required by the bot

upload_document

Upload a raw text document to a Knowledge Base

upload_file_url

Upload an external file URL to Coze storage

Example Prompts for Coze in LlamaIndex

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

"Chat with bot 'bot_123' and ask 'Tell me about the history of Tokyo'."

"List all active workspaces in my Coze account."

"Upload the content of 'manual.txt' to dataset 'ds_999'."

Troubleshooting Coze MCP Server with LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Coze + LlamaIndex FAQ

Common questions about integrating Coze 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.