Supercharge your AI with Camunda (BPMN Engine). Control complex workflows through conversation.
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Camunda (BPMN Engine) MCP lets your AI agent orchestrate complex business processes using BPMN standards. You can start new workflows, monitor real-time incidents, assign human tasks, and retrieve process definitions—all without leaving your chat client.
It gives you conversational control over operational workflow execution.
What your AI can do
Activate jobs
Marks jobs for workers as active so they can be processed.
Assign user task
Assigns a required human task to a specific user account.
Complete job
Marks an activated job instance as successfully completed.
Initiate new workflows and track the status of existing process instances.
Locate, assign, and complete pending tasks that require human intervention to move a workflow forward.
Search for system incidents and jobs to quickly identify process bottlenecks or failures in real time.
Retrieve the full XML definitions of processes or search through deployed models to understand the underlying logic.
Check the cluster topology and job status directly, confirming all nodes are online and functional.
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Camunda (BPMN Engine) - 25 Tools
These tools give you direct access to every operational aspect of the BPMN process engine, letting you manage processes from start to finish through natural language commands.
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Start using Camunda (BPMN Engine) on VinkiusActivate Jobs
Marks jobs for workers as active so they can be processed.
Assign User Task
Assigns a required human task to a specific user account.
Complete Job
Marks an activated job instance as successfully completed.
Complete User Task
Completes a human task, allowing the workflow to proceed using provided variables.
Deploy Resources
Deploys new BPMN, DMN, or Form resources into the running process engine.
Fail Job
Manually marks a job as failed; this action often triggers retries or alerts.
Get Incident
Retrieves detailed information about a specific process incident.
Get Process Definition Xml
Fetches the raw BPMN XML definition for a specified process model.
Get Process Instance
Retrieves all current status details for an active or completed process instance.
Get Topology
Returns the cluster topology, showing which nodes are online and how they connect.
Get User Task Form
Retrieves the associated form data linked to a pending user task.
Get User Task
Gets specific details for a single user task instance.
Get Variable
Pulls the current value of any process or local variable by name.
Search Groups
Finds and lists available user groups within the system.
Search Incidents
Searches for specific process incidents based on criteria like date or severity.
Search Jobs
Runs a query to find job instances matching specified search parameters.
Search Process Definitions
Searches through all deployed process definitions by name or criteria.
Search Process Instances
Queries and lists process instances based on current state or variables.
Search Tenants
Finds and filters available tenants for multi-tenant applications.
Search User Tasks
Searches across all active user tasks to find pending items assigned to users or...
Search Users
Finds and lists available user accounts by name or email.
Search Variables
Searches the entire process memory for specific variable names or values.
Start Process Instance
Initiates a brand new workflow instance, allowing you to pass initial data variables.
Throw Job Error
Manually simulates an error condition within a job worker for testing purposes.
Unassign User Task
Removes a user task assignment, returning the item to an unassigned state.
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Claude AI
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Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.
Add Custom Connector
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 25 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
The workflow status checks you currently manage by clicking through tabs.
Right now, checking if an order is stuck requires a tedious dance: log into the service dashboard, find the process instance ID, check the task queue to see who needs to act, and then jump to the incident dashboard to figure out *why* it's stalled. It’s always three or four tabs open.
With this MCP, you talk to your agent. You ask, 'What happened with order 550?' The system immediately compiles data from the instance details, checks for pending tasks via `search_user_tasks`, and surfaces any related incidents using `get_incident`. It’s all in one chat window.
The Camunda (BPMN Engine) MCP gives you full process control.
You eliminate the need to manually run reports on job status or check if a node is online. Instead, running `search_jobs` and then checking `get_topology` provides immediate operational visibility; you know system health from one simple query.
What's different now is control. You move from reactive dashboard monitoring to proactive orchestration. Your agent lets you manage the whole lifecycle—from starting a process instance with variables via `start_process_instance` to completing a user task and confirming success.
What your AI can actually do with this
Managing complex business logic used to mean jumping between three different dashboards: the modeler, the task queue, and the incident log. Now, your AI agent handles it all. Connect this MCP through Vinkius, and treat your entire process suite like a single API endpoint. You can initiate new processes with specific variables; if that process hits a snag, you don't wait for an alert—you ask your agent to find and inspect the incident details immediately.
Need to get work done? Your agent searches for pending tasks assigned to you and handles completion. This isn't just monitoring; it’s active orchestration from your IDE or chat client.
019e3874-0548-73d5-96c9-cdebe0ac19ec 
Here's how it actually works
The bottom line is: you manage complex workflows conversationally, treating your process engine like an extension of your terminal.
Subscribe to this MCP and provide your Camunda Base URL and Bearer Token.
Reference a specific process need with your agent (e.g., 'Find all failed jobs for the fulfillment service').
Your agent runs the necessary tool calls, returns structured data on incidents or tasks, and presents a simple summary in the chat.
Who is this actually for?
Anyone whose job relies on understanding or moving multi-step business processes. This is for the Ops Engineer who gets sick of switching between dashboards; the Developer who needs to test flow logic locally; and the Process Analyst who needs an immediate view of system bottlenecks.
Checks get_topology or runs search_jobs when a service degrades, needing instant visibility into job failures before they impact users.
Uses the MCP to manually start and complete test process instances, validating new business logic without deploying code changes.
Searches for incidents (search_incidents) or inspects definitions using get_process_definition_xml to map out current operational flows and identify gaps.
What Changes When You Connect
You don't need to jump between the Modeler and Operate dashboards. Your AI agent acts as a single technical process orchestrator, letting you inspect definitions using get_process_definition_xml directly in chat.
When things break, find them instantly. Instead of navigating incident logs, use search_incidents or run get_incident to get the specific root cause and status summary immediately.
Manage human input effortlessly. You can search for all pending tasks using search_user_tasks, then assign one with assign_user_task, and finally complete it with complete_user_task—all in a conversational flow.
Debugging is faster than ever. Need to know why a job failed? Use get_process_instance or check the cluster health using get_topology for immediate system status confirmation.
Testing new flows is streamlined. You can start process instances with specific data variables (start_process_instance) and then simulate failure by running throw_job_error, all within a controlled test run.
See it in action
Incident Response (Ops)
The fulfillment system is failing. Instead of logging into the Operate dashboard, the engineer asks their agent to search_incidents. The agent returns a list, and by running get_incident on the key ID, they instantly see which step failed and why.
Feature Development (Dev)
A developer needs to test how an order fulfillment process handles payment failure. They use their agent to run start_process_instance with a specific variable set, then manually trigger a job error using throw_job_error to validate the retry logic.
Workflow Audit (BA)
A business analyst wants to know what steps are in place for 'Invoice Approval.' They ask their agent to retrieve the XML definition using get_process_definition_xml, getting the full technical map without touching any UI.
User Management (Ops)
A manager needs to track all outstanding tasks for a department. The agent runs search_user_tasks across the entire system, giving them a list of pending items and who needs to act on them.
The honest tradeoffs
Checking status via dashboard
The process is stuck. I'll just log into the Operate UI and click through dashboards until I find the stalled instance.
Don't navigate UIs. Ask your agent to search_process_instances or use get_incident first. The MCP pulls that status data directly to you.
Manual variable lookup
I need the order ID from step three, but I have to click on the instance details page just to copy one variable.
Just ask your agent: 'What is the value of orderId for process instance X?' Use get_variable and get the answer instantly.
Assuming system health
The job failed, so I'll assume the cluster is okay until someone complains.
Don't guess. Run get_topology. This immediately tells you if nodes are partitioned or if the cluster state is compromised.
When It Fits, When It Doesn't
Use this MCP if your business logic requires managing complex, multi-step workflows where human interaction and system failures are expected parts of the process (e.g., finance approvals, order fulfillment). The core value is turning dashboard navigation into conversational commands.
Don't use it if you just need to read a single database record or fetch simple static data; dedicated query tools handle that better. Also, avoid using this for pure model versioning; stick to search_process_definitions when you only need to check what models are deployed, and save the heavy lifting of starting processes for start_process_instance.
It's designed for control plane operations—monitoring state changes, managing tasks, and debugging flows. It isn't a data warehouse or a simple CRUD tool.
Questions you might have
How do I check if a specific job failed using activate_jobs? +
You don't use activate_jobs to check for failures. Use search_jobs first, and then run get_incident on the resulting IDs to determine why it failed.
Can I start a new process instance using start_process_instance? +
Yes. You simply tell your agent you want to start a process (e.g., 'Start order fulfillment for ID 123'). The tool handles the initiation and passes the necessary variables.
What is the difference between search_user_tasks and get_user_task? +
search_user_tasks finds all pending tasks across the system, letting you scope your query (e.g., by user or group). get_user_task retrieves the full detail for one specific task ID.
If I need to know what variables are in a process, should I use get_variable? +
Yes, that's the right call. Use get_variable and provide the name of the variable you want. It returns its current value within the specified process context.
How do I change who is responsible for a task using assign_user_task? +
You use assign_user_task to re-route ownership. This function lets you take an existing user task and immediately assign it to a different specific user, managing the assignment history automatically.
If I suspect process failures, how do I find them using search_incidents? +
Run search_incidents to pinpoint workflow breakdowns. This tool allows you to filter incidents by time or job ID, giving you the exact details needed to troubleshoot a failing business process step.
What is the command for updating and deploying new BPMN models? +
deploy_resources handles all model updates. You call this tool to push new BPMN, DMN, or Form definitions into the Camunda engine, making them available for use in running processes.
How can I check the overall health of my Camunda cluster? +
Use get_topology to monitor system health. This function pulls data on your entire cluster's topology and partition status, letting you see if all nodes are connected and operating correctly.
Can I start a process instance with specific input data? +
Yes! Use the start_process_instance tool and provide the variables JSON object. The AI will map your data to the process requirements automatically.
How do I find all tasks currently assigned to a specific user? +
You can use the search_user_tasks tool with a filter like {"assignee": "user-id"}. The agent will return a list of all active human tasks for that person.
Is it possible to see why a process instance is stuck? +
Yes. Use search_incidents to find errors in the cluster, and then get_incident with the specific key to see the error message and stack trace.
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