MCP For Claude Marketplace
Axiom

Axiom MCP Connector for Claude

F

Manage logs and observability data via Axiom — ingest data, run APL queries, and manage datasets or monitors directly from any AI agent.

31 tools Official Updated Jun 28, 2026 Official Vinkius Partner
More Details Connect to Claude

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

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.

How it works

  1. Subscribe to this server
  2. Enter your Axiom API Token and optional Organization ID
  3. Start analyzing your logs and managing infrastructure from Claude, Cursor, or any MCP-compatible client

Who is this for?

  • DevOps & SREs — instantly query logs for errors, check monitor statuses, and manage alerts without leaving the terminal or chat.
  • Software Engineers — debug production issues by running APL queries directly from the code editor to find specific trace IDs or logs.
  • Data Analysts — ingest and analyze large datasets using Axiom's powerful processing language through simple natural language prompts.
telemetrylog-analysisreal-time-monitoringdata-ingestionapl-queriescloud-observability

31 tools expose this connector's capabilities to your AI agent.

create_annotation

Create a new annotation

create_dashboard

Create a new dashboard

create_dataset

Create a new dataset

create_monitor

Create a new monitor

create_notifier

Create a new notifier

delete_annotation

Delete an annotation

delete_dashboard

Delete a dashboard

delete_dataset

Delete a dataset

delete_monitor

Delete a monitor

delete_notifier

Delete a notifier

get_annotation

Retrieve a specific annotation by ID

get_dashboard

Retrieve a specific dashboard by UID

get_dataset

Retrieve a specific dataset by ID

get_monitor

Retrieve a specific monitor by ID

get_notifier

Retrieve a specific notifier by ID

get_org

Retrieve an organization by ID

get_user

Retrieve a specific user by ID

ingest_data

Ingest data into an Axiom dataset

list_annotations

List all annotations

list_dashboards

List all dashboards

list_datasets

List all datasets

list_monitors

List all monitors

list_notifiers

List all notifiers

list_tokens

List all API tokens

list_users

List all users

run_query

Run an APL query against Axiom data

update_annotation

Update an existing annotation

update_dashboard

Update an existing dashboard

update_dataset

Update an existing dataset

update_monitor

Update an existing monitor

update_notifier

Update an existing notifier

See how to talk to your AI agent using Axiom.

List all my available Axiom datasets.

I've retrieved your datasets. You have 3 active datasets: 'production-logs' (ID: ds_123), 'staging-metrics' (ID: ds_456), and 'security-audit' (ID: ds_789).

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

Executing query: `['production-logs'] | where level == 'error' | summarize count()`... I found 142 error events in the specified timeframe. Would you like to see the specific error messages?

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

I've created the 'High Latency' monitor. It will run every 5 minutes using your APL query to detect threshold breaches. Monitor ID: mon_abc123.

Yes! Use the `run_query` tool to execute any APL string. You can specify `start_time` and `end_time` to filter your data and get precise analytical results directly in the chat.

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