Summit MCP server

Bring Summit's conversion-audit insights into your coding agent. HandClaude Code / Codex / Gemini CLI a Summit audit and have it implement the fixes — grounded inreal CRO analysis with exact selectors and before→after copy.

Install

Nothing to install — any MCP client can launch it straight from npm:

npx -y @antmind-ai/summit-mcp

Or install the summit-mcp command globally:

npm install -g @antmind-ai/summit-mcp

Requires Node.js ≥ 18.17.

Tools

Tool	What it does
`summit_get_audit(report)`	Fetch an audit by share token or link. Returns score/grade, what the business is, a screenshot URL, and ranked findings (selector, current vs suggested copy, rationale, estimated lift).
`summit_implementation_plan(report)`	Turn the audit into an ordered, code-ready checklist — each step has a priority tier, selector, action, before→after, and expected lift.
`summit_list_findings(report, tier)`	Findings filtered to one tier (`must_fix` / `should_fix` / `nice_to_fix`).
`summit_run_audit(url, email)`	Kick off a new audit (1 free per email). Returns a share link to poll.
`summit_list_sites()` (auth)	Sites in your workspace.
`summit_list_experiments(site_id)` (auth)	Experiments + status/winner.
`summit_workspace_overview()` (auth)	KPI rollup: visitors/conversions (7d), running experiments, pending reviews, winners shipped.
`summit_review_queue()` (auth)	Everything waiting on human sign-off — proposed findings + built experiments.
`summit_approve_finding(finding_id)` (auth, mutates)	Approve a fix → builds an A/B experiment + variants (Pro).
`summit_reject_finding(finding_id)` (auth, mutates)	Dismiss a proposed fix.
`summit_approve_experiment(experiment_id)` (auth, mutates)	Approve a built experiment for launch.
`summit_launch_experiment(experiment_id)` (auth, mutates)	Start serving the A/B test live.
`summit_experiment_results(experiment_id)` (auth)	Bayesian verdict: leader, lift, P(beat control), significance.
`summit_site_pulse(site_id)` (auth)	Snippet install check + 7-day visitors/conversions/rage clicks.

The first four work off a public share token — no auth required. The workspace tools needSUMMIT_API_TOKEN + SUMMIT_WORKSPACE_ID and cover the full Study → Approve → Ship loop, soan agent can go from audit to launched experiment to measured result without leaving the editor.Tools marked mutates change workspace state (they never touch your live site directly — variantsonly serve after an experiment is explicitly launched).

Getting the two workspace values (a Pro feature — minting a token requires a paid plan):sign in and open Settings → Summit MCP tokens in the app to generate SUMMIT_API_TOKEN (shownonce) and copy your SUMMIT_WORKSPACE_ID. The web docs attrysummit.ai/docs walk through it and pre-fill the config with yourworkspace ID. A token is scoped to a single workspace and can be revoked anytime.

Configuration (env)

Var	Default	Notes
`SUMMIT_API_BASE_URL`	`http://localhost:8000`	Summit backend root (the server appends `/api/v1`). Use `https://api.trysummit.ai` for production.
`SUMMIT_API_TOKEN`	–	Bearer token for the workspace tools. Generate in Settings → Summit MCP tokens (Pro). Optional — omit for audit-only.
`SUMMIT_WORKSPACE_ID`	–	Workspace UUID for the workspace tools (shown next to the token in Settings). Optional — omit for audit-only.
`SUMMIT_HTTP_TIMEOUT`	`30`	Per-request timeout (seconds).

Register with your agent

The audit tools work with just SUMMIT_API_BASE_URL. To unlock the workspace loop, addSUMMIT_API_TOKEN + SUMMIT_WORKSPACE_ID (from Settings → Summit MCP tokens; see above).

Claude Code

claude mcp add summit \
  --env SUMMIT_API_BASE_URL=https://api.trysummit.ai \
  --env SUMMIT_API_TOKEN=smt_your_token_here \
  --env SUMMIT_WORKSPACE_ID=your_workspace_id \
  -- npx -y @antmind-ai/summit-mcp

Codex CLI — `~/.codex/config.toml`

[mcp_servers.summit]
command = "npx"
args = ["-y", "@antmind-ai/summit-mcp"]
env = { SUMMIT_API_BASE_URL = "https://api.trysummit.ai", SUMMIT_API_TOKEN = "smt_your_token_here", SUMMIT_WORKSPACE_ID = "your_workspace_id" }

Gemini CLI — `~/.gemini/settings.json`

{
  "mcpServers": {
    "summit": {
      "command": "npx",
      "args": ["-y", "@antmind-ai/summit-mcp"],
      "env": {
        "SUMMIT_API_BASE_URL": "https://api.trysummit.ai",
        "SUMMIT_API_TOKEN": "smt_your_token_here",
        "SUMMIT_WORKSPACE_ID": "your_workspace_id"
      }
    }
  }
}

(Any MCP-aware client works — point it at npx -y @antmind-ai/summit-mcp, or at the summit-mcp command ifinstalled globally, over stdio. Omit the token + workspace-id envs to use just the free audit tools.)

Example agent flow

You: Audit https://moonsign.co.in and fix the top 3 conversion issues.

Agent → summit_run_audit(url="https://moonsign.co.in", email="[email protected]")
      ← { share_url: ".../audit?r=TOK", status: "queued" }
Agent → summit_implementation_plan(report="TOK")     # poll until completed
      ← { steps: [ { selector: "a.cta", before: "Learn more",
                     after: "Get my free reading", expected_lift_pct: 12 }, … ] }
Agent then edits the codebase per each step.

Or drive the whole loop against your workspace (auth env vars set):

You: Anything waiting on me? Approve the highest-lift fix and launch it.

Agent → summit_review_queue()
      ← { findings: [ { id: "…", title: "Weak hero CTA", estimated_lift: 14, … } ], experiments: [] }
Agent → summit_approve_finding(finding_id="…")        # builds experiment + variants
Agent → summit_approve_experiment(experiment_id="…")  # after QA
Agent → summit_launch_experiment(experiment_id="…")
      … later …
Agent → summit_experiment_results(experiment_id="…")
      ← { winner_key: "b", leader_prob: 0.97, is_significant: true }

Develop

npm install
npm test          # node:test — pure transforms + mocked-fetch tool tests, no network

The package is plain ESM JavaScript with no build step. Runtime dependencies are just@modelcontextprotocol/sdk and zod.

License

MIT

Summit MCP server