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SemVer Version Manager MCP Server for LlamaIndexGive LlamaIndex instant access to 2 tools to Check Semver Compatibility and Sort Semver List

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LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add SemVer Version Manager 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 for LlamaIndex

The SemVer Version Manager MCP Server for LlamaIndex is a standout in the Productivity category — giving your AI agent 2 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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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 SemVer Version Manager. "
            "You have 2 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in SemVer Version Manager?"
    )
    print(response)

asyncio.run(main())
SemVer Version Manager
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About SemVer Version Manager MCP Server

LLMs hallucinate software versions. They constantly fail to evaluate complex semantic version boundaries (like `>=1.4.0

LlamaIndex agents combine SemVer Version Manager tool responses with indexed documents for comprehensive, grounded answers. Connect 2 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.

The SemVer Version Manager MCP Server exposes 2 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 2 SemVer Version Manager tools available for LlamaIndex

When LlamaIndex connects to SemVer Version Manager through Vinkius, your AI agent gets direct access to every tool listed below — spanning semantic-versioning, dependency-management, software-lifecycle, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

check

Check semver compatibility on SemVer Version Manager

Checks if a specific version satisfies a SemVer range (e.g. ^1.4.2)

sort

Sort semver list on SemVer Version Manager

Pass both versions and receive the comparison result (greater, lesser, equal). Essential for dependency resolution. Sorts a JSON array of version strings correctly following semantic versioning rules

Connect SemVer Version Manager to LlamaIndex via MCP

Follow these steps to wire SemVer Version Manager into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 2 tools from SemVer Version Manager

Why Use LlamaIndex with the SemVer Version Manager MCP Server

LlamaIndex provides unique advantages when paired with SemVer Version Manager through the Model Context Protocol.

01

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

02

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

03

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

04

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

SemVer Version Manager + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the SemVer Version Manager MCP Server delivers measurable value.

01

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

02

Data enrichment: query SemVer Version Manager to augment indexed data with live information before generating user-facing responses

03

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying SemVer Version Manager for fresh data

04

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

Example Prompts for SemVer Version Manager in LlamaIndex

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

01

"Verify deterministically if version `2.4.1` satisfies the peer dependency range `^2.0.0`."

02

"Sort this array of 12 release tags (including `-rc.1` and `-beta`) in descending order."

03

"What is the result of applying a 'minor' bump to version `1.4.3-alpha`?"

Troubleshooting SemVer Version Manager MCP Server with LlamaIndex

Common issues when connecting SemVer Version Manager to LlamaIndex through Vinkius, and how to resolve them.

01

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

SemVer Version Manager + LlamaIndex FAQ

Common questions about integrating SemVer Version Manager MCP Server with LlamaIndex.

01

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.
02

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query SemVer Version Manager tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
03

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

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