Fastn MCP. Manage and execute complex backend workflows instantly.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Fastn MCP connects your AI agent to a low-code backend engine, letting you manage complex business logic without writing code.
You can trigger flows instantly, build and update workflow definitions, track execution history step by step, or securely handle API credentials directly from conversation.
This is for running real-world, multi-step processes.
What your AI agents can do
Archive workflow
Deactivates a workflow definition, preventing it from running accidentally.
Cancel execution
Stops an active flow run immediately if it's taking too long or failed mid-process.
Create workflow
Builds a brand new, blank workflow definition blueprint.
Instantly triggers complex, multi-step backend processes using custom data payloads.
Allows you to list, create, and update the blueprints for your business logic flows.
Provides full, step-by-step logs of completed or failed runs so you can debug processes.
Stores and rotates API keys and secrets required for third-party connections.
Retrieves real-time data on your platform usage against set limits.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Fastn: 16 Tools for Flow Control
Use these tools to manage workflow definitions, track execution history, update credentials, or trigger real-time backend processes.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Fastn on Vinkius019e3893archive workflow
Deactivates a workflow definition, preventing it from running accidentally.
019e3893cancel execution
Stops an active flow run immediately if it's taking too long or failed mid-process.
019e3893create workflow
Builds a brand new, blank workflow definition blueprint.
019e3893execute flow
Runs an existing flow immediately using real-time data payloads.
019e3893get credentials
Retrieves stored API keys and connection details for third-party services.
019e3893get execution
Fetches the entire, detailed step-by-step history of a single flow run.
019e3893get quota daily
Shows how much usage you've consumed today against your plan limit.
019e3893get quota summary
Retrieves a high-level summary of all platform usage metrics.
019e3893get quota usage
Checks your current consumption level compared to the overall plan limits.
019e3893get workflow
Retrieves the full, detailed specifications of an existing workflow definition for review.
019e3893list executions
Provides a list and basic status overview of past flow runs for your tenant.
019e3893list workflows
Returns an inventory listing all available workflow definitions in the environment.
019e3893publish workflow
Makes a draft workflow definition live and ready for external execution.
019e3893rotate credentials
Generates new API keys, keeping your connection secrets fresh and secure.
019e3893store credentials
Adds and saves sensitive third-party access credentials to the platform.
019e3893update workflow
Modifies existing workflow definitions before they are published or used.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Fastn, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,000+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Fastn. 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.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
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 server provides 16 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
The Pain of Context Switching
Right now, if a new customer signs up, your process looks like this: You trigger the webhook, which sends data to an endpoint. Then you have to open the logging dashboard to check for success. Next, you manually copy the user ID and paste it into the CRM interface. Finally, you switch tabs to the email service to send the welcome message. It’s a painful sequence of clicks and copies.
With this MCP, your agent handles that whole mess in one go. You simply tell your agent: 'Onboard new user XYZ.' The agent manages the data flow: it calls the CRM API, sends the confirmation email, and logs everything—all without you ever leaving your conversation window.
Getting Full Visibility with Fastn MCP
The biggest time sink is figuring out *why* something failed. Today, if a flow breaks, you get a generic error code and maybe one line of log text saying 'step 3 failed.' You then have to manually trace back through logs in different systems just to figure out which data point was wrong.
Now, when a workflow fails, the agent gives you the full execution history. You use tools like `get_execution` to see every step's input and output, showing exactly where the process stopped and why. It makes debugging reliable and fast.
What you can do with this MCP connector
Need to run a complicated backend process? Instead of manually calling multiple endpoints or clicking through five different dashboards, you tell your agent what needs to happen using plain language. The MCP handles the rest. You can define entire workflows—like processing an order from start to finish—and execute them with a single prompt.
If that fails halfway through, you don't just get an error code; you get a full history of every step and why it broke. This capability means your business logic stays centralized and auditable. Connect this MCP via the Vinkius catalog, and your agent gains the power to manage sophisticated operational tasks, letting you focus on what you want done instead of how to connect all the APIs.
019e3894-0f7f-709a-862f-104e1cd22b05 
How Fastn MCP Works
- 1 First, subscribe to this MCP and provide the required Fastn API Key and Space ID.
- 2 Next, use your AI agent client to call specific tools; for instance, requesting a list of active workflows or initiating an execution run.
- 3 Finally, receive real-time results—either the immediate output payload from a successful flow or detailed step-by-step logs if something breaks.
The bottom line is you manage and execute complex backend logic using conversation instead of writing API wrappers.
Who Is Fastn MCP For?
This MCP serves the developer who needs to test business logic without leaving their IDE, the DevOps engineer managing credentials programmatically, or product teams needing verifiable execution status.
You use this MCP to build and test new flow definitions (create_workflow, update_workflow) and deploy them safely via the agent without switching context from your code editor.
You monitor execution traces, check usage limits (get_quota_summary), and manage sensitive environment credentials programmatically using dedicated tools.
When a user story requires backend action (like 'send welcome email' or 'process payment'), you use the agent to trigger that specific business flow (execute_flow) and check its success status.
What Changes When You Connect
- Instead of manually calling multiple endpoints, you can trigger flows directly using
execute_flowby simply describing the required business action to your agent. The complexity vanishes. - You don't have to guess if a flow is ready. Use
list_workflowsto see every available definition andget_workflowto inspect its exact parameters before you publish it withpublish_workflow. - If an execution fails, you get more than just 'Error 500.' You use
get_executionto drill down into the step-by-step trace, telling you exactly which function failed and why. This cuts debugging time by hours. - Credential security is handled automatically. Use
store_credentialsto save secrets, then runrotate_credentialsregularly so your keys never expire or get compromised. - You always know if the process can even run. Before executing, check quotas using
get_quota_usageandget_quota_summaryto prevent unexpected failures due to hitting limits.
Real-World Use Cases
Processing a new user sign-up
A product team needs to ensure that when a user signs up, three things happen: an email is sent, their profile is created in the CRM, and a welcome event is logged. Instead of writing one large function handling all three APIs, they use execute_flow against a pre-built 'onboarding' flow definition.
Auditing failed nightly data syncs
A DevOps engineer notices that the daily Salesforce to internal database sync failed. They don't know where it broke, so they use list_executions to find the run ID and then call get_execution to trace back through every single step until the failure point is clear.
Updating core business rules
The billing department changes how tax rates are calculated. Rather than deploying a new microservice, they use get_workflow to pull the existing 'invoice generation' flow definition, make minor adjustments using update_workflow, and then push the change live via publish_workflow.
Securing API access for a new service
A developer needs to connect the system to an entirely new payment gateway. They first use store_credentials to save the necessary key, then they tell their agent to update the relevant flow definition using update_workflow so it can access that new credential.
The Tradeoffs
Relying on single-shot calls
Trying to execute a complex process by just calling one API endpoint and expecting all side effects (logging, CRM updates) to happen automatically. This leaves the entire system brittle.
→
Always define the full sequence of actions in a workflow blueprint first. Use create_workflow to build the definition, review it with get_workflow, and then initiate the whole process using execute_flow. This guarantees transaction integrity.
Using old credentials
The flow runs fine for weeks, but suddenly fails because a third-party service rotated its key. The developer misses the failure until an urgent business moment.
→
Treat your secrets as perishable goods. Use store_credentials to save them and schedule regular key refreshment using rotate_credentials. Never assume old keys are still valid.
Running without checking quotas
The product team initiates a large batch run, only for the process to fail abruptly with an 'exceeded quota' error, causing immediate operational disruption.
→
Check resource availability first. Before running any high-volume job, check your plan status using get_quota_usage. This prevents costly failures and gives you time to raise limits.
When It Fits, When It Doesn't
Use this MCP if your business logic is inherently multi-step, requires strict auditability, or involves sensitive credentials. You need a verifiable 'state machine' for your processes; simply calling one API endpoint isn't enough. Use it when you must guarantee that Step B only runs after Step A completes successfully, and you need proof of the intermediate steps. Don't use this if all you need is to read data or perform a single, isolated calculation—a simple database query tool will suffice. When in doubt about process reliability, always mandate reviewing the workflow definition using get_workflow before attempting any deployment with publish_workflow.
Common Questions About Fastn MCP
How do I check if a workflow definition is correct before publishing it? (Using get_workflow) +
You use get_workflow to pull the full specification. This lets you review every single parameter and logic gate without risking an incomplete or faulty deployment.
What if I need to run a flow right now, but it's too big? (Using execute_flow) +
Use execute_flow with the necessary input payload. If you suspect resource limits, always check your quota first using get_quota_usage before running large batches.
I need to change a flow definition; do I have to redeploy everything? (Using update_workflow) +
No. You use update_workflow to make targeted changes to the existing blueprint, and then you only publish those specific modifications via publish_workflow. This keeps your core logic stable.
How do I secure my keys for a new service? (Using store_credentials) +
You use store_credentials to save the API key. The agent then references these stored secrets whenever it runs an execution, so you don't have to handle the raw keys directly.
How do I debug a failed flow run using the `get_execution` tool? +
The get_execution tool provides a full step-by-step trace. This lets you see exactly which step failed and why, so you can pinpoint the error without running multiple test cycles.
If I need to pause development on a flow, how do I use `archive_workflow`? +
archive_workflow deactivates the flow immediately. It keeps the definition safe in your account but prevents accidental execution until you manually decide to publish it again.
How can I check my current usage and remaining API calls using `get_quota_usage`? +
get_quota_usage provides a clear breakdown of your consumption against your plan limits. This is crucial for managing billing expectations before launching any large-scale campaigns.
When should I use the `rotate_credentials` function? +
You run rotate_credentials regularly to refresh your API keys. Doing this minimizes risk if an old credential is ever compromised, keeping your backend systems secure over time.
Can I trigger a flow and get the result immediately? +
Yes. Use the execute_flow tool with the flow name and input data. It performs a real-time sync execution and returns the response directly to the agent.
How can I debug a failed flow execution? +
You can use list_executions to find the ID of the failed run, then use get_execution to retrieve a full step-by-step trace of what happened during that specific execution.
Is it possible to update an existing workflow definition? +
Absolutely. The update_workflow tool allows you to modify the JSON definition of any flow. Remember to use publish_workflow afterwards to deploy your changes to the live environment.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.