How to Use the Honeybadger (Error Tracking) MCP in CrewAI

Q: How can I assign different Honeybadger (Error Tracking) tools to different agents in CrewAI?

When you configure your MCPServerHTTP toolset in CrewAI, use the toolfilter parameter. This lets you create different toolsets for each agent, for example, giving a 'resolveragent' access to resolvefault while a 'monitoragent' only gets read-only tools.

Q: Can a CrewAI team monitor multiple projects in Honeybadger (Error Tracking)?

Absolutely. A 'Planner' agent can start by calling listprojects to get a list of all project IDs. It can then delegate the task of checking each project to a series of 'Monitor' agents, running them in parallel.

Deploy a crew of autonomous agents to monitor, triage, and resolve Honeybadger errors with CrewAI. Assign roles, share context, and run on autopilot.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Honeybadger (Error Tracking) MCP to CrewAI

Create your Vinkius account to connect Honeybadger (Error Tracking) to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Honeybadger (Error Tracking) with CrewAI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

An Autonomous DevOps Crew

Don't just run one agent, run a team. Assign a 'Monitor' agent the `list_faults` and `list_sites` tools. Its only job is to watch for new errors or downtime in your projects. When the Monitor agent finds a new fault, it passes the fault ID to a 'Triage' agent. This second agent uses `get_fault` and `list_notices` to gather deep context, like the stack trace and recent occurrences. It then decides if the fault is critical.

Role-Based Fault Resolution with CrewAI

The Triage agent can't fix things itself. If it identifies a critical issue, it passes the context to a 'Resolver' agent. This is the only agent in the crew granted access to the `resolve_fault` tool. This separation of duties is a core CrewAI pattern. This MCP Server makes it easy to set up. When you define your CrewAI agents, you use the `tool_filter` to give each agent only the tools it needs. This prevents an analysis agent from accidentally resolving a production fault.

Correlate Deployments with a 'Historian' Agent

Add a 'Historian' agent to your crew. Its job is to use the `list_deployments` tool to keep track of what code has been shipped and when. It provides this context to other agents. Now, when the Monitor agent finds a new error, it can ask the Historian: 'Was there a deployment in the last 10 minutes?' The crew now has the context to determine if a rollback might be necessary, all without a human intervening.

Setup guide

Set up Honeybadger (Error Tracking) MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Honeybadger (Error Tracking) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Honeybadger (Error Tracking) Analyst",
    goal="Access and analyze Honeybadger (Error Tracking) data via MCP.",
    backstory="Expert analyst with direct Honeybadger (Error Tracking) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Honeybadger (Error Tracking) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Honeybadger (Error Tracking) Analyst",
        goal="Access and analyze Honeybadger (Error Tracking) data via MCP.",
        backstory="Expert analyst with direct Honeybadger (Error Tracking) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Honeybadger (Error Tracking) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Honeybadger. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Honeybadger (Error Tracking) now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Honeybadger (Error Tracking) MCP in CrewAI

When you configure your `MCPServerHTTP` toolset in CrewAI, use the `tool_filter` parameter. This lets you create different toolsets for each agent, for example, giving a 'resolver_agent' access to `resolve_fault` while a 'monitor_agent' only gets read-only tools.

Absolutely. A 'Planner' agent can start by calling `list_projects` to get a list of all project IDs. It can then delegate the task of checking each project to a series of 'Monitor' agents, running them in parallel.

A simple crew would have two agents. Agent 1 (Monitor) uses `list_faults`. If it finds a new fault, it passes the ID to Agent 2 (Analyst). The Analyst uses `get_fault` to investigate and reports its findings.

It provides the essential data for triage: fault class name, error message, the environment, number of occurrences, and when it was first and last seen. It's the perfect starting point for an autonomous monitoring agent using this MCP connection.

Only your authenticated agents. The connection is proxied through a Vinkius MCP server, which runs in an ephemeral sandbox. Your fault details and project data are never persisted or logged by our systems.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript