Convex MCP Server for LangChainGive LangChain instant access to 4 tools to Run Action, Run Function, Run Mutation, and more

Name: Convex
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LangChain is the leading Python framework for composable LLM applications. Connect Convex through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Ask AI about this MCP Server for LangChain

Open in ChatGPT Open in Claude Open in Perplexity

The Convex MCP Server for LangChain is a standout in the Loved By Devs category — giving your AI agent 4 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "convex": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Convex, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

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 Convex MCP Server

Connect your Convex deployment to any AI agent and manage your application's data and logic through natural conversation. This server allows you to interact with your real-time database and serverless functions without leaving your AI interface.

LangChain's ecosystem of 500+ components combines seamlessly with Convex through native MCP adapters. Connect 4 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Data Fetching — Execute read-only queries to retrieve documents and state from your Convex tables.
Transactional Updates — Run mutations to modify data with full ACID guarantees directly from the agent.
Side Effects & APIs — Trigger Convex actions for external API calls, heavy computation, or non-transactional logic.
Flexible Execution — Call functions using standard colon notation or URL-style identifiers for maximum compatibility.

The Convex MCP Server exposes 4 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 4 Convex tools available for LangChain

When LangChain connects to Convex through Vinkius, your AI agent gets direct access to every tool listed below — spanning real-time-database, serverless-functions, typescript, 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.

run

Run action on Convex

Call a Convex action function

run

Run function on Convex

g., "messages/list" instead of "messages:list"). Call a Convex function by its URL identifier

run

Run mutation on Convex

Call a Convex mutation function

run

Run query on Convex

Use this for fetching data. Call a Convex query function

Connect Convex to LangChain via MCP

Follow these steps to wire Convex into LangChain. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 4 tools from Convex via MCP

Why Use LangChain with the Convex MCP Server

LangChain provides unique advantages when paired with Convex through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Convex MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Convex queries for multi-turn workflows

Convex + LangChain Use Cases

Practical scenarios where LangChain combined with the Convex MCP Server delivers measurable value.

RAG with live data: combine Convex tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Convex, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Convex tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Convex tool call, measure latency, and optimize your agent's performance

Example Prompts for Convex in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Convex immediately.

"Run the Convex query 'messages:list' with no arguments."

"Call the mutation 'users:create' with the argument { "name": "Alice" }."

"Execute the function 'tasks/get_all' using run_function."

Troubleshooting Convex MCP Server with LangChain

Common issues when connecting Convex to LangChain through Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Convex + LangChain FAQ

Common questions about integrating Convex MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.