Bring Telemetry
to CrewAI
Learn how to connect Axiom to CrewAI and start using 31 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Axiom MCP Server?
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
- Subscribe to this server
- Enter your Axiom API Token and optional Organization ID
- 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.
Built-in capabilities (31)
Create a new annotation
Create a new dashboard
Create a new dataset
Create a new monitor
Create a new notifier
Delete an annotation
Delete a dashboard
Delete a dataset
Delete a monitor
Delete a notifier
Retrieve a specific annotation by ID
Retrieve a specific dashboard by UID
Retrieve a specific dataset by ID
Retrieve a specific monitor by ID
Retrieve a specific notifier by ID
Retrieve an organization by ID
Retrieve a specific user by ID
Ingest data into an Axiom dataset
List all annotations
List all dashboards
List all datasets
List all monitors
List all notifiers
List all API tokens
List all users
Run an APL query against Axiom data
Update an existing annotation
Update an existing dashboard
Update an existing dataset
Update an existing monitor
Update an existing notifier
Why CrewAI?
When paired with CrewAI, Axiom becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Axiom tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
- —
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
- —
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Axiom in CrewAI
Axiom and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Axiom to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Axiom in CrewAI
The Axiom 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. All 31 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Axiom for CrewAI
Every tool call from CrewAI to the Axiom MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I run complex log analysis using Axiom Processing Language (APL)?
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.
How do I send new log data to my Axiom datasets?
You can use the ingest_data tool. Simply provide the dataset_name, the data payload, and the content_type (JSON, NDJSON, or CSV) to stream data into your Axiom account.
Is it possible to manage system monitors and alerts through this integration?
Absolutely. You have access to a full suite of tools including list_monitors, create_monitor, and update_monitor to configure threshold or anomaly detection alerts based on your APL queries.
How does CrewAI discover and connect to MCP tools?
CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
Can different agents in the same crew use different MCP servers?
Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
What happens when an MCP tool call fails during a crew run?
CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
Can CrewAI agents call multiple MCP tools in parallel?
CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
Can I run CrewAI crews on a schedule (cron)?
Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
Rate limiting or 429 errors
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.
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