@sheepit-ai/mcp

Let Claude, Cursor, and Codex drive your Sheepit project from the IDE.

A Model Context Protocol server that gives your AI coding assistant direct control of your Sheepit project — campaigns, flags, experiments, dashboards, releases, and insights queries — without leaving the editor.

Why it exists

Sheepit holds your flags, experiments, growth campaigns, and product analytics. Acting on any of it normally means switching to the dashboard, clicking through forms, and copying values back to your code. This server removes that round-trip: the assistant already in your IDE reads and writes Sheepit for you. One sheepit login authenticates both the CLI and this MCP server, so there is no second key to manage and every action the assistant takes is auditable.

Related MCP server: task-orchestrator

Example

After installing (below), restart your IDE and ask your assistant in plain language:

You: Launch the "Fall Promo" email campaign, but show me a preview first.

The assistant calls campaign_preview, shows you the rendered subject and body plus the audience size, and waits. The preview returns a single-use token; campaign_launch requires that token, so the assistant physically cannot send a campaign you have not seen.

You: Did signups dip yesterday?

The assistant calls insights_query against your event stream and answers with the number, no dashboard needed.

You: Roll out the new-checkout flag to 10% of users.

The assistant calls flag_get to read the current state, then flag_update to set the rollout.

How it works

1. sheepit login runs a PKCE OAuth flow in your browser and writes ~/.sheepit/credentials.json.

2. sheepit-mcp install writes an MCP server entry into your IDE's config file (backing up the existing file first).

3. You restart your IDE. It launches sheepit-mcp serve over stdio.

4. The server reads ~/.sheepit/credentials.json (or SHEEPIT_API_KEY from the environment) and authenticates to the Sheepit API.

5. The assistant calls tools/list and discovers every available tool. New sessions should call sheepit_help first for an overview.

6. When you ask for something, the assistant calls the matching tool. Every input is validated with Zod at request time, so an out-of-date client gets a structured error instead of silent drift.

Install

Three commands. The first two are real, published packages (@sheepit-ai/cli, @sheepit-ai/mcp).

# 1. One-time OAuth login (opens your browser)
npx @sheepit-ai/cli login

# 2. Write the MCP entry into your IDE config.
#    The first command is a dry run; the second applies it.
npx @sheepit-ai/mcp install
npx @sheepit-ai/mcp install --yes

# 3. Restart your IDE, then ask: "what can I do with Sheepit?"

install auto-detects your client. To target one explicitly:

npx @sheepit-ai/mcp install --yes --client=claude-desktop   # Claude Desktop
npx @sheepit-ai/mcp install --yes --client=cursor           # Cursor
npx @sheepit-ai/mcp install --yes --client=codex            # Codex

install is idempotent (re-running with the entry already present is a no-op), backs up the existing config to <path>.bak.<unix-ms>.<pid>.<rand> (mode 0600) before writing, writes atomically via tmp+rename, and refuses to follow symlinks. Upgrading from a pre-1.0 @goatech/mcp install replaces the old mcpServers.goatech entry with mcpServers.sheepit in place.

CLI reference

sheepit-mcp serve                              # default — stdio MCP server
sheepit-mcp install                            # dry run: show what would change
sheepit-mcp install --yes                      # apply
sheepit-mcp install --force                    # overwrite an existing entry
sheepit-mcp install --client=claude-desktop    # (or cursor | codex)
sheepit-mcp version
sheepit-mcp help

Tools

49 tools across 10 surfaces. The count is generated from the source at build time (src/generated/build-meta.ts), so it does not drift from the registry.

Start with sheepit_help for a guided overview, or sheepit_quickstart with one of send_email_campaign, create_dashboard, analyze_signups, ship_feedback, wire_webhook_destination for a concrete step-by-step recipe.

Two extra meta-tools (search_tools, load_tool) appear only in on-demand loading mode (below) and are excluded from the count.

On-demand tool loading (experimental, opt-in)

By default the server advertises all tools, so their schemas load into your assistant's context every session. Set SHEEPIT_MCP_LAZY_TOOLS=1 to advertise only a small core set plus two discovery tools (search_tools, load_tool); the rest stay callable but load their schemas on demand, which cuts upfront tool-schema context substantially. When the assistant needs a tool that is not listed, it calls search_tools to find it and load_tool to fetch its schema, then calls it by name.

SHEEPIT_MCP_LAZY_TOOLS=1   # advertise core + discovery tools only (default: off)

This is off by default while both modes are measured (the $mcp_tools_listed event carries lazy, advertised_count, and schema_bytes).

Telemetry and opt-out

The server emits coarse, non-PII usage events ($mcp_session_started, $mcp_tools_listed, $mcp_tool_invoked, $mcp_session_ended) to your own project so you can see how the MCP is used and where it fails. Events carry the tool name, success or failure, duration, and a coarse error code only. They never carry your tool arguments, query bodies, or any customer data.

To turn telemetry off, set either of these in the environment the server runs in (your IDE's mcpServers.sheepit.env, or your shell):

DO_NOT_TRACK=1          # the cross-vendor consoledonottrack.com convention
SHEEPIT_TELEMETRY=0     # Sheepit-specific switch (also accepts =false)

When either is set, the emit short-circuits to a no-op. Telemetry already never throws and never blocks your tool calls; the opt-out stops the emit entirely.

FAQ

Is this published? Yes. @sheepit-ai/mcp is on npm (latest 1.0.1, MIT-licensed). The npx commands above resolve against the real package.

Which clients are supported? Claude Desktop, Cursor, and Codex out of the box. The server speaks standard MCP over stdio, so any MCP-compatible client can run sheepit-mcp serve with a manual config entry.

Do I need a Sheepit account? Yes. sheepit login authenticates against your Sheepit project. The same credentials file powers both the CLI and this server.

Does it send my data anywhere? Only coarse, non-PII usage events to your own project, and you can turn those off (see Telemetry and opt-out). Tool arguments and query results are never included.

I'm on @goatech/mcp. How do I upgrade? See Upgrading from @goatech/mcp below.

Where's the source? github.com/sheepit-ai/sheepit-mcp.

Upgrading from @goatech/mcp

1.0.0 renamed the package from @goatech/mcp to @sheepit-ai/mcp as part of the Sheepit product rebrand. The legal entity (GoaTech AI LLC) is unchanged; the npm scope is the customer-facing brand. This is a hard cutover with no legacy fallback:

To migrate:

1. Update your IDE config + any npx invocations to @sheepit-ai/mcp. Running sheepit-mcp install --yes detects and migrates the old mcpServers.goatech key automatically.

2. Move your credentials: mv ~/.goatech/credentials.json ~/.sheepit/credentials.json, or just re-run sheepit login.

3. Rename any GOATECH_* env vars to SHEEPIT_*. The old names are not honored as fallbacks.

Restarting your IDE re-discovers the new tool names from tools/list, so no further client change is needed.

What did not change: the API URL (api.goatech.ai), the API key prefix (lp_pub_* / lp_sec_*, which scopes production data and customer .env files), and the legal entity name (GoaTech AI LLC, used on invoices and contracts).

Versioning

This package follows Sheepit product releases. A major-version bump signals either the MCP protocol moving or a breaking change to the API surface the tools wrap (as in 1.0.0, an npm-scope rename). Tool inputs are validated with Zod at request time, so an out-of-date client gets a structured error rather than silent drift.

License

MIT. Copyright (c) 2026 GoaTech AI LLC. See LICENSE.