Alpic MCP Server for LlamaIndex 18 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Alpic as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Alpic. "
"You have 18 tools available."
),
)
response = await agent.run(
"What tools are available in Alpic?"
)
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 Alpic MCP Server
What you can do
Connect AI agents to the Alpic platform for complete MCP server lifecycle management:
LlamaIndex agents combine Alpic tool responses with indexed documents for comprehensive, grounded answers. Connect 18 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.
- List and manage teams with member access controls
- Create, update, and delete MCP server projects with git repository linking
- Deploy to multiple environments (dev, staging, production) with one command
- Monitor deployments with real-time status, logs, and analytics
- Manage environment variables securely for each deployment target
- View analytics including request counts, latency, error rates, and usage patterns
- Publish to the MCP registry to make your servers discoverable
- Create development tunnels for local testing before production deployment
The Alpic MCP Server exposes 18 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 Alpic to LlamaIndex via MCP
Follow these steps to integrate the Alpic 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 18 tools from Alpic
Why Use LlamaIndex with the Alpic MCP Server
LlamaIndex provides unique advantages when paired with Alpic through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Alpic tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Alpic tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Alpic, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Alpic tools were called, what data was returned, and how it influenced the final answer
Alpic + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Alpic MCP Server delivers measurable value.
Hybrid search: combine Alpic real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Alpic 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 Alpic for fresh data
Analytical workflows: chain Alpic queries with LlamaIndex's data connectors to build multi-source analytical reports
Alpic MCP Tools for LlamaIndex (18)
These 18 tools become available when you connect Alpic to LlamaIndex via MCP:
add_variable
Use this to set API keys, database URLs, feature flags, or any configuration needed by your MCP server. Requires project ID, environment ID, variable key, and value. Variable values are stored securely. Add a new environment variable to an Alpic environment
create_environment
Requires environment name and project ID. Optionally set initial variables and configuration. Each environment gets a unique URL for MCP client connections. Returns the created environment details. Create a new deployment environment (dev, staging, prod) for an Alpic project
create_project
Requires project name and team ID. Optionally set description, repository URL, and initial configuration. Returns the created project details including the new project ID needed for subsequent operations. Create a new MCP server project in Alpic
delete_project
This action cannot be undone. Use with caution. Requires the project ID. Confirm with the user before proceeding. Delete an Alpic MCP server project
delete_variable
Use this to clean up unused configuration keys. Requires project ID, environment ID, and variable key. Delete an environment variable from an Alpic environment
deploy_environment
The deployment runs asynchronously. Returns the deployment ID which can be used with get_deployment to check status. Use this to push new MCP server versions to dev, staging, or production environments. Trigger a new deployment for a specific Alpic environment
get_deployment
Requires the deployment ID. Use this to check if a deployment succeeded, review deployment history, or debug failed deployments. Get detailed status and metadata for a specific Alpic deployment
get_deployment_logs
Useful for debugging failed deployments, understanding build output, or verifying successful startup of the MCP server. Requires project ID and environment ID. Get deployment logs for a specific Alpic environment
get_project
Requires the project ID from list_projects results. Use this to review project settings before making updates or triggering deployments. Get detailed information about a specific Alpic MCP server project
get_project_analytics
Requires the project ID. Use this to monitor MCP server health, identify performance trends, and troubleshoot issues. Get analytics and usage data for a specific Alpic project
get_server_info
Use this to verify which MCP tools are exposed and confirm the server is running correctly. Get server information and status for a specific Alpic project
get_tunnel_ticket
Returns the tunnel URL and ticket token. Use this during development to test your MCP server before deploying to a production environment. Get a tunnel ticket for local development and testing of an MCP server
list_environments
Each environment has its own URL, variables, and deployment status. Returns environment IDs, names, URLs, and current deployment state. Use this to identify which environment to deploy to or manage variables for. List all environments (dev, staging, prod) for a specific Alpic project
list_projects
Returns project IDs, names, descriptions, associated teams, deployment status, and environment counts. Use this to overview your entire MCP infrastructure before managing specific projects or triggering deployments. List all MCP server projects in your Alpic account
list_teams
Each team contains projects and environments for deploying MCP servers. Returns team IDs, names, and member counts. Use this first to identify which team to manage projects under. List all teams associated with your Alpic account
list_variables
Variable values are masked for security. Returns variable keys and metadata. Use this to audit environment configuration before deploying or adding new variables. List all environment variables configured for an Alpic environment
publish_to_registry
Requires project ID and optionally a server description and category. Use this to make your MCP server publicly available. Publish an MCP server to the official MCP registry via Alpic
update_project
Only pass the fields you want to change. Requires the project ID from list_projects results. Use this to rename projects, update descriptions, or point to a new repository branch. Update an existing Alpic MCP server project configuration
Example Prompts for Alpic in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Alpic immediately.
"List all active Alpic projects running on my account natively, then check the error rate metric for the first one listed."
"Deploy the staging environment for our main enterprise project mapped on isolated branches."
"Audit the credentials in our production environment. Provide exact details of variable schemas missing from active lists."
Troubleshooting Alpic MCP Server with LlamaIndex
Common issues when connecting Alpic to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAlpic + LlamaIndex FAQ
Common questions about integrating Alpic 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 Alpic 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 Alpic to LlamaIndex
Get your token, paste the configuration, and start using 18 tools in under 2 minutes. No API key management needed.