Axiom MCP Server for LangChainGive LangChain instant access to 31 tools to Create Annotation, Create Dashboard, Create Dataset, and more

Name: Axiom
Price: 29 USD
Availability: InStock
Rating: 2.2 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The Axiom MCP Server for LangChain is a standout in the Data Analytics category — giving your AI agent 31 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

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ChatGPT

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VS Code

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+ 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({
        "axiom": {
            "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 Axiom, 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 Axiom MCP Server

Connect your Axiom account to any AI agent to streamline your observability and log management workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Axiom through native MCP adapters. Connect 31 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 Ingestion & Querying — Ingest JSON, NDJSON, or CSV data and run complex Axiom Processing Language (APL) queries to analyze logs in real-time.
Dataset Management — List, create, and update datasets to organize your telemetry and infrastructure data efficiently.
Monitoring & Alerts — Manage monitors and notifiers to stay informed about system performance, errors, and anomalies.
Dashboards & Annotations — Access dashboards and create annotations to visualize trends and mark significant system events.
Organization Insights — Retrieve user information, API tokens, and organization details to maintain secure and authorized access.

The Axiom MCP Server exposes 31 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 31 Axiom tools available for LangChain

When LangChain connects to Axiom through Vinkius, your AI agent gets direct access to every tool listed below — spanning telemetry, log-analysis, real-time-monitoring, 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.

create

Create annotation on Axiom

Create a new annotation

create

Create dashboard on Axiom

Create a new dashboard

create

Create dataset on Axiom

Create a new dataset

create

Create monitor on Axiom

Create a new monitor

create

Create notifier on Axiom

Create a new notifier

delete

Delete annotation on Axiom

Delete an annotation

delete

Delete dashboard on Axiom

Delete a dashboard

delete

Delete dataset on Axiom

Delete a dataset

delete

Delete monitor on Axiom

Delete a monitor

delete

Delete notifier on Axiom

Delete a notifier

get

Get annotation on Axiom

Retrieve a specific annotation by ID

get

Get dashboard on Axiom

Retrieve a specific dashboard by UID

get

Get dataset on Axiom

Retrieve a specific dataset by ID

get

Get monitor on Axiom

Retrieve a specific monitor by ID

get

Get notifier on Axiom

Retrieve a specific notifier by ID

get

Get org on Axiom

Retrieve an organization by ID

get

Get user on Axiom

Retrieve a specific user by ID

ingest

Ingest data on Axiom

Ingest data into an Axiom dataset

list

List annotations on Axiom

List all annotations

list

List dashboards on Axiom

List all dashboards

list

List datasets on Axiom

List all datasets

list

List monitors on Axiom

List all monitors

list

List notifiers on Axiom

List all notifiers

list

List tokens on Axiom

List all API tokens

list

List users on Axiom

List all users

run

Run query on Axiom

Run an APL query against Axiom data

update

Update annotation on Axiom

Update an existing annotation

update

Update dashboard on Axiom

Update an existing dashboard

update

Update dataset on Axiom

Update an existing dataset

update

Update monitor on Axiom

Update an existing monitor

update

Update notifier on Axiom

Update an existing notifier

Connect Axiom to LangChain via MCP

Follow these steps to wire Axiom 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 31 tools from Axiom via MCP

Why Use LangChain with the Axiom MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine Axiom 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 Axiom queries for multi-turn workflows

Axiom + LangChain Use Cases

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

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

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

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

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

Example Prompts for Axiom in LangChain

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

"List all my available Axiom datasets."

"Run an APL query to count errors in 'production-logs' from the last 24 hours."

"Create a new monitor named 'High Latency' that checks for response times over 500ms."

Troubleshooting Axiom MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Axiom + LangChain FAQ

Common questions about integrating Axiom 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.

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

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