Coassemble MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Coassemble 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 Coassemble. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in Coassemble?"
)
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 Coassemble MCP Server
Connect your Coassemble account to any AI agent and take full control of your online training and LMS through natural conversation. Streamline how you manage learners, courses, and completion results natively.
LlamaIndex agents combine Coassemble tool responses with indexed documents for comprehensive, grounded answers. Connect 8 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
- Course Oversight — List and retrieve details for all training courses in your workspace natively
- Enrolment Intelligence — Access and monitor student enrolments and their current progress flawlessly
- Member Management — List all workspace members and their contact details securely
- Group Logistics — Monitor student groups and manage their course associations flawlessly
- Completion Auditing — Retrieve training results and grades for all enrolments to track success flawlessly
- Profile Visibility — Access your own user profile and core workspace metadata directly within your workspace
The Coassemble MCP Server exposes 8 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 Coassemble to LlamaIndex via MCP
Follow these steps to integrate the Coassemble 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 8 tools from Coassemble
Why Use LlamaIndex with the Coassemble MCP Server
LlamaIndex provides unique advantages when paired with Coassemble through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Coassemble tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Coassemble tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Coassemble, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Coassemble tools were called, what data was returned, and how it influenced the final answer
Coassemble + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Coassemble MCP Server delivers measurable value.
Hybrid search: combine Coassemble real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Coassemble 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 Coassemble for fresh data
Analytical workflows: chain Coassemble queries with LlamaIndex's data connectors to build multi-source analytical reports
Coassemble MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect Coassemble to LlamaIndex via MCP:
enroll_member_in_course
Enroll a specific member into a course or group
get_course_training_details
Get detailed information for a specific course
get_member_group_associations
Get all groups a specific member belongs to
get_training_completion_results
List training results and grades for enrolments
list_coassemble_courses
List all training courses in the Coassemble workspace
list_coassemble_enrolments
List all course enrolments
list_coassemble_groups
List all student groups in the workspace
list_coassemble_members
List all members (users) in the workspace
Example Prompts for Coassemble in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Coassemble immediately.
"List all training courses in my Coassemble workspace."
"Show me the progress for user 'STU_12345'."
"What are the latest completion results?"
Troubleshooting Coassemble MCP Server with LlamaIndex
Common issues when connecting Coassemble to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCoassemble + LlamaIndex FAQ
Common questions about integrating Coassemble 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 Coassemble 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 Coassemble to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.