Skyvern
Skyvern automates browser-based workflows with AI agents that can navigate websites, extract data, and complete tasks.
Verdict
Common use cases
- Check scraping job status during standups
- Cancel stuck workflow runs in bulk
- Pull error logs from failed automations
- Organize agents into folders by client
- Audit recent runs before deploying changes
Integration
- Vendor
- Skyvern
- Category
- other
- Auth
- API_KEY
- Tools
- 10
- Composio slug
skyvern
Tools
- Cancel Runs
Cancel one or more active task or workflow runs in one request and report which IDs succeeded or failed.
- Create Folder
Create a folder for organizing Skyvern agents.
- Delete Folderdestructive
Delete a Skyvern folder without deleting the agents it contains.
- Get Folder
Get one Skyvern folder by ID, including its current agent count.
- Get Run
Get current status, output, errors, files, and observation links for a task or workflow run.
- List Agents
Search and list the latest versions of Skyvern agents available to the connected organization.
- List Folders
Search and list folders used to organize Skyvern agents.
- List Runs
Find task and workflow runs for the connected organization, with status, type, workflow, and text filters.
- Start Browser Task
Start an autonomous browser task that can navigate and interact with websites, including clicking and submitting forms. It may cause external side effects and consume Skyvern credits; use GET_RUN to monitor it and CANCEL_RUNS to stop it.
- Update Folder
Change the title or description of an existing Skyvern folder.
Setup
Setup guide
- 11. In Switchy, open Settings and navigate to the Integrations page. 2. Find Skyvern in the MCP directory and click Connect. 3. Log into your Skyvern account and copy an API key from the API settings page. 4. Paste the key into Switchy's prompt and click Authorize. 5. Switchy confirms the connection and shows which tools are now available. 6. Open any Project, type '@Skyvern list runs' in the chat, and send — if you see a table of recent task or workflow runs, the integration works. 7. Use '@Skyvern get run' with a run ID to fetch detailed status, output files, and error messages for any job.
What teammates see: by default, memories from Skyvern are scoped to the Project (PROJECT visibility) - you can mark any memory PRIVATE or share it ORG-wide.
Works well with
Top models
Compatibility data appears once enough Projects have used this MCP together with a given model.
How Switchy teams use it
Starter prompts
Check Recent Runs
@Skyvern list the last 10 runs and show me their status, type, and when they started.
Get Run Details
@Skyvern get run details for ID abc123 and show me any errors or output files it generated.
Cancel Active Jobs
@Skyvern cancel runs with IDs xyz789 and def456, then confirm which ones stopped successfully.
List All Agents
@Skyvern list all agents and include their folder assignments and latest version numbers.
Organize Folders
@Skyvern create a folder called 'Client Onboarding' and move agents A, B, and C into it.
Example outputs
Illustrative - representative of the model's voice and quality, not literal recordings.
@Skyvern list all agents in the 'customer-onboarding' folder and show me which ones have run in the last 7 days
Found 4 agents in the 'customer-onboarding' folder. Two have recent activity: 'Verify Email Agent' (last run 2 days ago, completed successfully) and 'Document Upload Agent' (last run 5 days ago, failed with timeout). The other two agents—'Welcome Survey Agent' and 'Payment Setup Agent'—have not run in the past week. All agents are on their latest versions.
This example combines folder lookup with run history filtering to surface agent usage patterns. Requires read access to both agents and runs. The MCP returns metadata only; you won't see the actual browser automation steps or screenshots unless you fetch a specific run's observation links.
@Skyvern cancel all runs that have been active for more than 30 minutes and show me which workflows were affected
Canceled 3 active runs that exceeded the 30-minute threshold. Affected workflows: 'Invoice Processing' (2 runs canceled, both stuck at login step) and 'Data Entry Workflow' (1 run canceled, mid-form submission). All cancellations succeeded. No runs under 30 minutes were touched. You may want to investigate why the Invoice Processing workflow is stalling at authentication.
This demonstrates bulk cancellation with filtering logic applied by the AI. Skyvern's Cancel Runs tool accepts multiple IDs in one request, but the MCP doesn't auto-detect 'stuck' runs—you define the criteria in your prompt. Canceling a run stops browser automation immediately and may leave external systems in incomplete states.
@Skyvern create a new folder called 'Q1-2025-Experiments' and move all agents tagged 'prototype' into it, then summarize what got moved
Created folder 'Q1-2025-Experiments' (ID: fld_x7k2m). Moved 5 agents tagged 'prototype': 'LinkedIn Scraper v2', 'Form Filler Test', 'Multi-Step Checkout', 'PDF Extractor Beta', and 'API Fallback Handler'. All agents remain at their current versions and retain their run history. The folder now contains 5 agents; no other folders were modified.
This example shows folder creation followed by agent organization. The MCP's Create Folder and List Agents tools don't directly support 'move' operations—the AI infers which agents match your criteria and you'd update them separately (Skyvern's API handles agent-folder association outside these read/write primitives). Useful for keeping experimental automations separate from production workflows.
Use-case deep-dives
When Skyvern beats manual scraping for weekly price checks
A 6-person e-commerce team needs to track competitor pricing across 20 sites every Monday morning. Skyvern wins here because the agents handle site structure changes without brittle selectors, and the folder system keeps pricing agents separate from checkout-testing agents. Use List Agents to audit what's deployed, then List Runs with status filters to catch failures before the pricing deck goes to leadership. The trade-off: if your competitors block automation or require CAPTCHA solving, Skyvern's agent approach still hits walls. This works when you're scraping public catalog pages at low frequency and can tolerate a 2-hour refresh window. If you need sub-minute pricing updates or are scraping login-gated content, evaluate whether the API_KEY scope covers your auth needs first.
How Skyvern fits end-to-end testing for small product teams
A 4-person SaaS team ships checkout changes weekly and wants to catch regressions before customers do. Skyvern is borderline here. The Get Run tool surfaces observation links and error logs, which beats screenshot-only tools when a test fails. Create Folder keeps staging agents separate from production monitors. But if your checkout has more than 8 steps or requires dynamic data (promo codes, inventory checks), you'll spend more time debugging agent runs than writing Playwright scripts. This makes sense when your flow is stable, changes are cosmetic, and you want to avoid maintaining selectors across redesigns. If your team already writes code-based tests or your checkout logic changes every sprint, stick with Playwright and save Skyvern for the competitor-monitoring use case.
When Skyvern handles repetitive form-filling for support teams
A 3-person support team processes 40 vendor RMA forms per week, each requiring 12 fields copied from Zendesk tickets. Skyvern wins when the forms are on third-party sites you don't control and the fields rarely change. Use List Runs to spot submission failures, then Cancel Runs to stop duplicate attempts when a vendor site goes down mid-batch. The folder system organizes agents by vendor, so onboarding a new RMA process doesn't pollute your existing setup. The limit: if the forms require file uploads from varied sources or multi-step approvals, the 10-tool API surface might not expose enough control. This works when the task is copy-paste-submit and you're doing it more than 10 times a week. Below that threshold, manual entry is faster than maintaining agents.
Frequently asked
What does the Skyvern MCP do in Switchy?
It lets your team trigger, monitor, and cancel Skyvern browser automation agents directly from Switchy conversations. You can list available agents, start task or workflow runs, check their status and output, and organize agents into folders—all without leaving the chat interface. Useful when you want an AI assistant to kick off web scraping or form-filling jobs on demand.
Do I need a Skyvern API key to connect this MCP?
Yes. The integration uses API key authentication, so you'll need to generate a key from your Skyvern organization settings and paste it into Switchy during setup. Anyone on your team with access to that key can connect the MCP; no OAuth dance or admin approval required.
Can the Skyvern MCP create or edit agents?
No. It can list existing agents, organize them into folders, and trigger runs, but it cannot create new agents or modify their workflows. If you need to build or update an agent, do that in the Skyvern web UI first, then use the MCP to execute it from Switchy.
Why use this instead of the Skyvern dashboard?
The MCP is faster when you want an AI assistant to launch a scraping job mid-conversation or check run status without context-switching. The dashboard is better for designing agents, debugging failed runs with screenshots, or reviewing detailed logs. Think of the MCP as a remote control, not a replacement.
Who on the team should connect the Skyvern MCP?
Whoever manages your Skyvern agents or needs to trigger automation runs from Switchy. Since it uses an API key, that person should already have access to your Skyvern organization. The connection doesn't count against Switchy seat limits, but Skyvern run usage still bills to your Skyvern account.