Run Teachfloor from your AI.
Connect Claude, ChatGPT, Gemini or any MCP client to Teachfloor. Pull data, build courses, enroll learners and run workflows — by prompt.
+ any MCP clientOne server. Every major AI client.
Built on the Model Context Protocol — the open standard for connecting AI assistants to real systems.
Built for the way teams work now.
No context switching
Manage Teachfloor from where your team already works — Claude, ChatGPT, Cursor. Skip the dashboard.
Orchestrate across your stack
Teachfloor becomes a callable tool inside multi-step workflows with Docs, Sheets, Slack and your CRM.
Live in minutes
Install once, authenticate via OAuth, done. No infrastructure to run, no maintenance burden.
Hundreds of workflows. Six to start.
Progress & completion
Pull org-wide or course-level progress in one prompt.
Show completion rate by cohort for the "Sales Onboarding" program this quarter.At-risk learners
Detect learners falling behind and draft a follow-up.
List learners under 40% progress in cohort #34 and draft a check-in email.Course from a PDF
Turn a PDF into a structured course with modules and lessons.
Create a course from this PDF and split it into 5 modules with quizzes.Automation builder
Wire trigger → filter → action across your stack.
Build an automation: when a learner completes the final quiz, assign the next course and post in Slack.Bulk enrollment
Enroll a list of learners into a cohort in one go.
Enroll all sales reps from this spreadsheet into the Q2 onboarding cohort.Certificate renewals
Surface expiring certificates and trigger reminders.
List certificates expiring in the next 30 days and email each owner a renewal link.From install to running, in three steps.
Install & connect
Add the Teachfloor MCP Server to your AI client. Authenticate via OAuth — no API keys to copy.
Your AI calls Teachfloor tools
Your prompt gets routed to the right tool — list courses, enroll learners, build automations, pull analytics.
Teachfloor executes & returns
Actions run with the permissions of the signed-in user. Results stream back to your AI in real time.
Common MCP questions.
Model Context Protocol is an open standard for connecting AI assistants to external systems. The Teachfloor MCP Server exposes Teachfloor capabilities — courses, learners, automations, analytics — as tools your AI can call.
Claude (Anthropic), ChatGPT (OpenAI), Gemini (Google), Microsoft Copilot, Cursor — and any other client that speaks MCP.
Minutes. Add the Teachfloor MCP Server to your AI client, sign in with your Teachfloor account, and start prompting. No API keys to copy or rotate.
OAuth 2.0 sign-in. Every action runs with the signed-in user's role and respects all Teachfloor permissions. Admins can disable specific tools per workspace.
Read and write across courses, modules, learners, cohorts, enrollments, certificates, automations, and analytics. The full surface area mirrors the Teachfloor API.
Yes. Every MCP call is recorded in your Teachfloor audit log with the user, action, timestamp, and result — exportable for compliance review.
Standard plan limits apply, the same as the REST API. Heavy workloads can request elevated limits through your account team.
Both. Admins can manage courses and learners; learners can ask their AI to surface progress, find materials, or join the next cohort — all scoped to their role.
Hosted by Teachfloor by default, with no infrastructure to run. Self-hosted deployments are available for Enterprise plans on request.
Bring Teachfloor into your AI workflow.
Install the MCP Server and run courses, learners and automations by prompt. Start today.