Sprig MCP is designed so an AI client sees only the survey data your Sprig role already permits, scoped by OAuth and enforced at every tool call. Agents can create studies in draft only, users approve before anything reaches respondents, and admins hold an org-wide kill switch. Unlike a CSV export, MCP leaves no permanent, unscoped copy of your data.
Data Handling and Retention
1. What happens to Sprig data inside the LLM conversation? Is it retained or used for training?
When your team prompts Sprig through MCP, the returned data becomes part of that conversation on the LLM provider's side. MCP introduces no new data exposure category beyond what your organization already accepted by adopting the LLM tool. Sprig does not store copies with the provider and does not control the provider's retention.
- In transit, tool calls run over TLS between the client and mcp.sprig.com.
- In context, the data lives inside the conversation for its duration.
- After the conversation, retention, training treatment, and provider-side access are governed by your organization's agreement with the LLM provider, not by Sprig.
2. Does Sprig or the LLM provider train models on our response data?
Sprig does not use your response data to train models. Data returned through MCP is subject to your LLM provider's own data handling terms, so enterprise customers should confirm their Claude, OpenAI, Gemini or Copilot agreement excludes training on API and connector traffic, which enterprise plans typically do.
3. How is MCP different from exporting a CSV and uploading it to an LLM?
A CSV export is a permanent, unscoped copy; MCP is scoped, live access with no lasting copy. Once a CSV is downloaded, it sits outside Sprig's permission model: anyone with the file can share it, upload it anywhere, and retain it indefinitely, with no way for you to revoke it. MCP inverts that. Data is fetched at prompt time, scoped to what the authenticated user is allowed to see, and access ends the moment an admin revokes the token or disables the server. A CSV upload is a one-time transfer with zero ongoing control; MCP is live access with your controls intact.
Access and Permissions
Sprig MCP lets AI clients, like Claude, ChatGPT, and Cursor, query your Sprig research data with no standing copy leaving Sprig. Access is scoped by OAuth to your existing Sprig role and enforced on every request. Agents draft studies but never launch them, admins can cut off all access instantly, and Sprig never trains on your responses.
- Permissions are checked at every tool call, not once at connection time.
- Agents create studies in draft state only.
- Admins can revoke all MCP connections org-wide, instantly, from one setting.
- Data returned into an LLM conversation follows your provider agreement, meaning enterprise plans from Anthropic, OpenAI, and Microsoft exclude it from model training.
4. What data can an LLM client access through Sprig MCP?
An LLM client can access aggregated and derived research data through Sprig MCP: surveys, responses, open-text themes, and response counts. It reaches this data at prompt time and only within the scope the authenticated user is allowed to see. The client does not receive a bulk export or a standing copy of your workspace.
5. How is access authenticated and controlled?
Every Sprig MCP connection runs through OAuth. Users authenticate with their own Sprig credentials, and the MCP server enforces the same role-based permissions as the Sprig app. A user cannot see data through Claude, ChatGPT, or Cursor that they could not see logged into Sprig directly. Because authorization is tied to the individual user's role, access reflects your existing Sprig permission model rather than a separate one.
6. How do LLM clients handle Sprig permissions on their side?
The LLM client never holds standing access to your Sprig workspace. It holds an OAuth token tied to one user, and every tool call is authorized against that user's Sprig permissions at request time. If a change is made to a user's role or their token is revoked, then the client's access changes with it. Admins on enterprise LLM plans also control which connectors are available to their org at all, adding a second permission layer on top of Sprig's.
Agent Actions and Control
7. Can an AI agent launch or modify live studies through MCP?
No. Sprig MCP exposes study creation in draft state only. A human reviews and approves every study in the Sprig app before it reaches respondents. MCP-created drafts are indicated as such, so your team can identify their origin during review. An agent cannot push a study live, change a running study, or reach respondents on its own.
8. What happens if we need to shut off access immediately?
Admins can turn the MCP server off from Integrations, AI & MCP in Sprig. This kill switch revokes all active connections org-wide, immediately, without waiting on individual users to disconnect their clients. It gives security and IT teams a single control to cut off all MCP access at once.
Connect your workspace to Sprig MCP at mcp.sprig.com/mcp.
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