About Outset
Outset connects AI agents to its AI-moderated research platform for study setup, recruitment, and results queries. Its remote server uses OAuth and enforces scopes and organization roles.
Key features
- 01Create and edit research studies
- 02Configure and launch participant recruitment
- 03Query reports, answers, and insights
- 04Access workspaces and organization details
Use cases
- 01Draft or revise a research study
- 02Set recruitment criteria and launch a study
- 03Review interview answers and topline insights
- 04Look up workspace or organization context
MCP support
The remote server is available over Streamable HTTP and uses OAuth 2.1 with PKCE and Dynamic Client Registration. It exposes tools for managing studies and recruitment, querying research results, and retrieving organization context.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://api.outset.ai/mcp/claude mcp add --transport http ai-outset https://api.outset.ai/mcp/{"mcpServers":{"ai-outset":{"type":"http","url":"https://api.outset.ai/mcp/"}}}Open in Cursor{"servers":{"ai-outset":{"type":"http","url":"https://api.outset.ai/mcp/"}}}Open in VS Code{"mcpServers":{"ai-outset":{"type":"http","url":"https://api.outset.ai/mcp/"}}}{"mcpServers":{"ai-outset":{"serverUrl":"https://api.outset.ai/mcp/"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEOutset MCP
Connect AI agents to Outset — the AI-moderated research platform — via the Model Context Protocol.
The Outset MCP server is remote: there is nothing to install or run. Point your MCP client at the endpoint below and log in with your Outset account.
https://api.outset.ai/mcp/
- Transport: Streamable HTTP (stateless JSON-RPC)
- Auth: OAuth 2.1 with PKCE + Dynamic Client Registration — compliant clients connect with zero pre-registration
- Full developer guide: Outset MCP — Integration Guide for Developers (OAuth flow, scopes, DCR details, testing)
Connect from your client
Claude (claude.ai / Desktop)
Settings → Connectors → Add custom connector, name it Outset, paste https://api.outset.ai/mcp/, then Connect to go through the OAuth consent flow. (Custom connectors require a Pro, Max, Team, or Enterprise plan.)
Claude Code
claude mcp add --transport http outset https://api.outset.ai/mcp/
Or install as a plugin from this repo:
claude plugin marketplace add Outset-AI/outset-mcp
claude plugin install outset@outset-mcp
Cursor
Or Settings → MCP → Add Server and paste the URL — Cursor handles registration and OAuth automatically.
ChatGPT
Enable Developer Mode under Settings → Apps & Connectors → Advanced settings, then Create a connector with https://api.outset.ai/mcp/ as the MCP server URL and OAuth as the auth method.
VS Code
code --add-mcp '{"name":"outset","type":"http","url":"https://api.outset.ai/mcp/"}'
Gemini CLI
gemini extensions install https://github.com/Outset-AI/outset-mcp
Codex
Add to ~/.codex/config.toml (or .codex/config.toml in your project):
[mcp_servers.outset]
url = "https://api.outset.ai/mcp/"
Then authenticate with:
codex mcp login outset
Anything else
Any MCP client that supports remote servers (Streamable HTTP + OAuth) works. For stdio-only clients, bridge with mcp-remote:
npx -y mcp-remote https://api.outset.ai/mcp/
To explore the tool list interactively:
npx @modelcontextprotocol/inspector https://api.outset.ai/mcp/
What your agent can do
- Create and edit studies — projects, sections, questions, screeners, display logic, quotas, concepts
- Configure and launch recruitment — sample size, reward, demographic filters (launching may incur fees and is gated behind the separate
studies:launchscope) - Query results — reports, answers, topline insights, category summaries, highlight clips
- Look up org context — workspaces, projects, organization info
The live tools/list response is the source of truth — new tools ship regularly. Scopes and org roles are enforced server-side; see the integration guide for the full scope table.
What's in this repo
Manifests for agent directories and marketplaces — the server itself is not here (it's remote):
| File | Purpose |
|---|---|
.claude-plugin/plugin.json + .mcp.json | Claude Code plugin wrapping the remote server |
.claude-plugin/marketplace.json | Makes this repo installable as a Claude Code plugin marketplace |
.cursor-plugin/marketplace.json | Same, for Cursor's plugin system |
gemini-extension.json | Gemini CLI extension (gemini extensions install <repo url>) |
server.json | Manifest for the official MCP registry |
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.