Flatchr

Live 29 Actions

Flatchr Integration for AI Agents

Connect your AI agent to 29 QA'd Flatchr actions via MCP, A2A, or SDK, with agent authentication, tool-calling execution, and security built-in.

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Flatchr AI Agent Actions

29 production-ready actions for your agent to do more on Flatchr.

Read the Flatchr docs

29 Actions

Retrieve Vacancies - List all vacancies (job ads) for your company.

Retrieve Active Vacancies - List the active, publicly published vacancies for your company career site.

Retrieve Vacancy - Get a single vacancy by its ID.

Create Vacancy - Create a new vacancy (job ad) for your company.

Search Candidates - Searches candidates (applicants) for a company in Flatchr using filters such as name, email, pipeline stage (column), job offer (vacancy), hired status and a creation date range.

Update Candidate Meta Information - Adds or updates meta information on an existing candidate (applicant) in Flatchr, identified by their email reference.

Move Candidate - Moves a candidate to a different column (pipeline stage) within a vacancy in Flatchr.

Archive Candidate - Archives (removes) a candidate from a vacancy in Flatchr.

Create Candidate (JSON) - Create a candidate application against a job vacancy using a JSON payload.

Create Candidate (Custom) - Create a candidate application against a job vacancy using a custom payload.

Create Candidate (Test) - Test candidate creation against a job vacancy without creating a real record.

Retrieve Candidate CV - Retrieves the downloadable CV document of a candidate in Flatchr using the unique CV key and file extension.

Retrieve Comments - Retrieve the comments left on a Flatchr applicant.

Create Comment - Create a comment on a Flatchr applicant.

Delete Comment - Delete a comment from a Flatchr applicant.

Retrieve Messages - Retrieve the messages exchanged with a Flatchr applicant.

Retrieve Tasks - List the recruitment tasks for the configured company.

Create Task - Create a recruitment task for the configured company.

Close Task - Close (mark as done) a recruitment task for the configured company.

Display Candidate Tags - Retrieve the tags attached to a Flatchr candidate.

Fill A Candidate Tag - Add a tag (trait) to a Flatchr candidate.

Retrieve Company Tags - List the tags configured for the company.

List Members - List the members (users) belonging to the company.

List Columns - Retrieve the columns (pipeline stages) configured for a company in Flatchr.

List Business Sectors - Retrieve the list of business sectors (industry categories) used in Flatchr.

List Channels - List the job board channels available for distributing vacancies in Flatchr.

List Channel Job Categories - List the job categories available for a specific channel in Flatchr.

List Contract Types - List the contract types reference data available in Flatchr.

List Education Levels - List the available education levels reference data from Flatchr.

Flatchr AI Agent Use Cases

Connect your AI agent to Flatchr and help your team scale the recruiting operations they run by hand today.

Job Posting Distribution

Use StackOne to connect your AI agent to your ATS and job boards to automate job posting distribution.

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Reference Check Automation

Use StackOne to connect your AI agent to your ATS, survey tools, and messaging systems to automate reference checks.

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Offer Letter Generation

Use StackOne to connect your AI agent to your ATS, HRIS, and document management tools to automate offer letter generation.

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More Recruiting use cases

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Integration Infrastructure for Flatchr AI Agents

Multiple Interfaces

Access integrations via API, AI SDKs, MCP & A2A.

Flatchr MCP server

Managed Authentication

Pre-built authentication UI.

Agent auth

Falcon Engine

Every Flatchr action runs on Falcon.

Agent Execution Engine

StackOne Defender

88.7% prompt injection detection.

Prompt injection defense

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"What impressed us most about StackOne is its ambition and clarity. They're creating infrastructure that modern software and the entire AI agent ecosystem can rely on. The depth of secure integrations, the pace of delivery, and the team's foresight into AI's future uniquely position StackOne to redefine this category."

Luna Schmid, Partner at GV

"We've been impressed by how quickly and deeply StackOne integrates with complex enterprise systems -- and now, with their focus on agent-to-agent interoperability, they're unlocking even more powerful use cases for customers. StackOne delivers all of the above in a universal layer -- without compromise."