Terac MCP
Connect any AI assistant or agent to Terac. Price studies, launch recruitment, and review submissions in plain language through the Model Context Protocol.
The Terac MCP server exposes Terac's API as a set of tools that any Model Context Protocol client can call. Connect Claude, Claude Code, Cursor, VS Code, or ChatGPT and your AI assistant can source verified experts, launch recruitment, and review work on your behalf, all in plain language.
Using Claude or ChatGPT? Terac is published in both directories, so it installs in one click with nothing to paste: Terac in Claude or Terac in ChatGPT. For every other client, see Install.
What You Can Do
Price any study
Describe who you need and submit a feasibility request. Our team prices it and returns a cost per participant before you commit any budget.
Launch recruitment
Turn a priced request into a live opportunity. Terac sources and screens matching experts automatically.
Target with filters
Narrow by verified demographic, geographic, and professional attributes instead of free-text descriptions.
Review and pay
List submissions, inspect the work, and approve or reject. Approved experts are paid automatically.
Endpoint
Connect your client to:
https://terac.com/api/mcp
The server speaks streamable HTTP and authenticates with either an organization API key or browser-based OAuth. See Install for client-by-client setup.
A Typical Flow
Once connected, ask your assistant to run the workflow end to end:
Always start a session by calling terac_get_context. It returns your organization identity, credit balance, projects, and policies, and grounds every tool call that follows.
Tool Catalog
The tools are grouped by what they touch. Each one carries full inline guidance that your assistant reads automatically, so you rarely need to name a tool yourself.
| Group | Tools |
|---|---|
| Organization | terac_get_context |
| Projects | terac_list_projects, terac_create_project, terac_get_project, terac_update_project |
| Targeting filters | terac_list_filters, terac_get_filter_options |
| Feasibility | terac_request_feasibility, terac_get_feasibility_request, terac_list_feasibility_requests |
| Drafts & launch | terac_create_opportunity, terac_update_opportunity, terac_launch_draft_opportunity, terac_delete_opportunity |
| Lifecycle | terac_list_opportunities, terac_get_opportunity, terac_pause_opportunity, terac_resume_opportunity, terac_stop_opportunity |
| Submissions | terac_get_submissions, terac_get_submission, terac_approve_submission, terac_reject_submission |
How Pricing Works
Pricing is not autonomous. terac_request_feasibility submits your audience and task to the Terac team; it does not return a price immediately. Your assistant then polls terac_get_feasibility_request until status is RESPONDED and costPerParticipant is set. A person prices it, typically within about an hour, longer for niche or multi-market audiences. Polling more often does not make it arrive sooner.
Once you have a price, build the study with terac_create_opportunity and take it live with terac_launch_draft_opportunity.
Safe by Design
Every tool is annotated so your client knows whether it reads or writes, and whether a write can be undone. Destructive actions (terac_stop_opportunity, terac_reject_submission, terac_delete_opportunity) are flagged so your client can ask you to confirm before running them.
There are no webhooks yet. To track progress, your assistant polls
terac_get_opportunity and terac_get_submissions rather than waiting for a
callback.