developer-toolsapi_key

Procfu

ProcFu enhances Podio's capabilities by providing a suite of automation tools and functions, enabling users to create scripts, mini apps, and integrate with various services to streamline workflows.

Verdict

Procfu exposes utility tools for data manipulation, file operations, and AI generation directly inside Switchy Spaces. @mention it to diff JSON arrays, sort lists, generate test data, create images via OpenAI, or manage Google Drive files without leaving your conversation. Developers and QA engineers get the most value — you can prototype data transformations, compare API responses, or spin up placeholder content on the fly. Auth requires an API key from Procfu's dashboard, and some tools (like Google Drive deletion) need additional OAuth scopes configured on their end.

Common use cases

  • Compare API response versions for breaking changes
  • Generate test datasets for QA workflows
  • Sort user lists before exporting reports
  • Create placeholder images for design mockups
  • Clean up Google Drive folders from chat

Integration

Vendor
Procfu
Category
developer-tools
Auth
API_KEY
Tools
11
Composio slug
procfu

Tools

  • Array Difference Deletions

    Tool to return items removed when comparing two JSON arrays. Use when you have two arrays and need to know which elements were deleted.

  • Array Diff New

    Tool to return items added in the second JSON array. Use when you need to identify new elements between two list versions. Example: Compare [1,3,4] vs [1,3,6] to get [6].

  • Array Diff Same

    Tool to get items present in both JSON arrays. Computes the intersection locally to avoid external API dependency. Rules: - Two items are considered equal if their JSON representations match (with sorted keys for objects). - The result cont

  • Array Sort

    Tool to sort a JSON array of values. Use when you need to order elements ascending or descending.

  • Ask question to OpenAI GPT

    Tool to ask a question to OpenAI GPT. Use when you need a conversational answer from GPT.

  • Delete Google Drive
    destructive

    Tool to delete a Google Drive file or folder. Use after obtaining a valid Google Drive ID.

  • Generate dummy data

    Tool to generate dummy data. Use when you need random emails, text, numbers, dates, people, addresses, or images for testing or placeholder data.

  • Generate Image with OpenAI

    Tool to generate an image via OpenAI API. Use when you need programmatic image creation from a text prompt.

  • Get Google Sheet contents as array

    Tool to get sheet contents as array. Use when you need to retrieve Google Sheet data as an associative array.

  • Get Google Sheets Metadata

    Tool to retrieve metadata of a Google Sheets spreadsheet, including sheet names, IDs, and properties. Use when you need sheet-level details for a given spreadsheet ID.

  • Google Drive Delete
    destructive

    Tool to delete a Google Drive file or folder. Use after obtaining a valid Google Drive ID.

Setup

Setup guide

  1. 11. In Switchy, open your workspace settings and navigate to the MCP Integrations tab. 2. Click 'Add Integration' and select Procfu from the developer tools category. 3. You'll be prompted to enter your Procfu API key — retrieve this from your Procfu account dashboard under API Settings. 4. Paste the key into Switchy and click 'Connect'. 5. Switchy will validate the key and confirm the connection within a few seconds. 6. Open any Space and type '@Procfu' to see available tools in the autocomplete menu. 7. Test the connection by running '@Procfu generate dummy data' with a simple request like 'give me 3 random email addresses'. 8. If the response returns mock data, the integration is live and ready for your team.

What teammates see: by default, memories from Procfu are scoped to the Space (PROJECT visibility) - you can mark any memory PRIVATE or share it ORG-wide.

Works well with

Top models

Compatibility data appears once enough Spaces have used this MCP together with a given model.

How Switchy teams use it

Not enough Spaces yet to publish anonymised usage stats (we require ≥ 50 Spaces per week).

Starter prompts

Diff Two JSON Arrays

@Procfu compare these two arrays and show me what changed: first array is ["user_123", "user_456", "user_789"] and second array is ["user_123", "user_999"].
Open in a Space →

Generate Test User Data

@Procfu generate 5 dummy user records with name, email, and phone number for our staging environment.
Open in a Space →

Sort a List Alphabetically

@Procfu sort this list of product names alphabetically: ["Zephyr", "Alpha", "Cascade", "Bravo"].
Open in a Space →

Create an Image from Text

@Procfu generate an image of a minimalist workspace with a laptop and coffee mug, suitable for a landing page hero section.
Open in a Space →

Ask GPT a Technical Question

@Procfu ask GPT: what's the difference between REST and GraphQL, and when should I use each?
Open in a Space →

Example outputs

Illustrative - representative of the model's voice and quality, not literal recordings.

Prompt

@procfu compare these two arrays and show me what was added: ["user-123", "user-456"] vs ["user-123", "user-456", "user-789", "user-012"]

Output

The Array Diff New tool identified 2 new items added in the second array: ["user-789", "user-012"]. These elements appear in the updated array but were not present in the original. This comparison is useful for tracking new user IDs, configuration changes, or any scenario where you need to audit additions between two list snapshots.

Notes

This example highlights Procfu's array-diffing capability, which runs locally without external API calls. Useful for quick data audits, but remember both arrays must be valid JSON. If your lists are large (thousands of items), consider performance implications of in-memory comparison.

Prompt

@procfu generate 10 fake user records with emails, names, and addresses for our staging environment test

Output

Generated 10 dummy user records: 1. alice.martinez@example.com, Alice Martinez, 742 Oak Street, Portland OR 2. james.chen@example.com, James Chen, 1583 Maple Ave, Austin TX [...8 more records...] Each record includes a randomized email, full name, and US address. This data is suitable for populating test databases or UI mockups without using real customer information.

Notes

The Generate Dummy Data tool is ideal for quickly scaffolding test fixtures without manual data entry. Procfu returns realistic-looking placeholders, but these are synthetic—don't use them in production or compliance-sensitive contexts. No rate limits mentioned, but large batch requests may take longer to process.

Prompt

@procfu delete the Google Drive folder with ID 1a2b3c4d5e6f7g8h9i after confirming it contains only outdated test files

Output

The Delete Google Drive tool successfully removed the folder with ID 1a2b3c4d5e6f7g8h9i. This action is permanent and cannot be undone through Procfu. If the folder contained nested files or subfolders, those were also deleted. Verify the folder is in your Google Drive trash if you need to recover it manually.

Notes

This example demonstrates Procfu's ability to perform destructive actions on external services. Requires valid Google Drive API credentials and appropriate OAuth scopes (drive.file or drive). Always double-check folder IDs before deletion—Procfu won't prompt for confirmation, and the MCP assumes you've already validated the target.

Use-case deep-dives

QA test data generation

When Procfu beats manual fixture creation for test suites

A 3-person QA team writing integration tests for a user-onboarding flow needs 200 realistic user profiles every sprint. Procfu's dummy-data generator wins here because it returns structured JSON (emails, addresses, dates) in one call, no CSV wrangling. The team pipes the output straight into their test harness and re-runs it weekly when fixtures go stale. The trade-off: if you need domain-specific data (medical codes, SKU formats), the generator won't know your schema—you'll still write custom factories. But for generic user attributes, Procfu cuts fixture-prep time from 90 minutes to under 5. If your test suite already has a mature factory library, skip this MCP. If you're copy-pasting from Mockaroo every week, Procfu is the faster path.

Changelog diff automation

How Procfu's array tools fit changelog-generation workflows

A solo dev maintaining an open-source CLI tool wants to auto-generate release notes by diffing the feature list between tags. Procfu's array-diff tools (deletions, new, same) handle the comparison in-memory, so you don't spin up a Python script or jq pipeline. The workflow: export feature arrays from two Git tags as JSON, call the diff tools, format the output into markdown. This works cleanly when your feature list lives in a structured file (JSON, YAML). The boundary: if your changelog logic needs semantic versioning rules or commit-message parsing, Procfu won't help—it's just array math. For small projects where the feature list is already JSON and you want one less script in the repo, Procfu keeps the release process inside your AI workspace.

Drive cleanup for offboarding

When Procfu's Drive-delete tool speeds up user offboarding

A 6-person ops team offboards contractors monthly and needs to purge their Google Drive folders without clicking through the web UI. Procfu's delete tool takes a Drive ID and removes the file or folder in one call. The win: you script the offboarding checklist (Slack archive, Drive purge, calendar cleanup) and run it from a shared Switchy workspace instead of a Zapier chain. The constraint: you still need the Drive ID upfront, so this pairs with a separate MCP or script that lists folder contents. If your offboarding volume is under 5 users per month, the web UI is faster. Above that threshold, Procfu turns a 20-minute manual task into a 2-minute scripted one, and the whole team can trigger it without admin access to a service account.

Frequently asked

What does the Procfu MCP do in Switchy?

Procfu gives your AI agents 11 utility tools for data manipulation and external API calls. The main use cases are comparing JSON arrays (finding added, removed, or common items), sorting data, generating test data (emails, names, addresses), and calling OpenAI's GPT or image generation APIs. It also includes a Google Drive deletion tool. Think of it as a Swiss Army knife for repetitive data tasks your agents would otherwise struggle with.

Do I need a Procfu account to use this MCP?

Yes. You need a Procfu API key, which means signing up at Procfu and generating credentials. Some tools (like array operations) run locally and don't hit Procfu's servers, but others (OpenAI calls, Google Drive actions) require a valid key. The setup is straightforward: paste your API key into Switchy's MCP settings and you're live.

Can this MCP write files to Google Drive or only delete them?

Only delete. The Google Drive tool removes files or folders by ID—it won't upload, create, or modify documents. If you need full Drive integration (read, write, share), use the official Google Drive MCP instead. Procfu's Drive tool is narrowly scoped for cleanup workflows, like purging test files after a batch job.

Why use Procfu instead of calling OpenAI or Drive APIs directly?

Procfu wraps common operations into single-step tools your AI can invoke without writing code. Comparing two arrays or generating dummy data would otherwise require your agent to write and execute Python or JavaScript. If you already have custom scripts for these tasks, you don't need Procfu. If you want agents to handle them conversationally, this MCP saves setup time.

Who on the team should connect the Procfu MCP?

Whoever manages your team's API keys and external integrations. The person connecting it will paste the Procfu API key into Switchy, so they need access to your Procfu account. Once connected, any team member can use the tools in their AI chats—no per-user auth required. It counts as one MCP connection against your Switchy plan.

Data last verified 607 hours ago.Sources aggregated hourly to weekly. See docs/architecture/model-directory.md.