bluealpha-incrementality-mcp 0.1.1

MCP server that helps marketing teams plan incrementality tests and hand off designs to BlueAlpha

bluealpha-incrementality-mcp

An MCP server that helps marketing teams plan incrementality tests through conversation — feasibility checks, business context capture, testing calendars, and handoff documents ready for your data science team to execute.

This is a planning tool, not a modelling tool. It helps marketers iterate on their first test design and package everything cleanly for BlueAlpha (or an internal data science team) to run the actual statistics: Causal Impact / BSTS, synthetic control, rigorous power analysis, post-test inference.

Why

Most marketers know they should run incrementality tests but get stuck at step one: "Am I even ready? What should I test? How do I explain it to my CMO or data team?" This server walks them through it — in plain language, no statistics jargon — and produces a handoff document that makes it trivial for a data science team to pick up the work.

Quick Start

Claude Desktop

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "incrementality": {
      "command": "uvx",
      "args": ["bluealpha-incrementality-mcp"]
    }
  }
}

Restart Claude Desktop.

Claude Code

claude mcp add incrementality -- uvx bluealpha-incrementality-mcp

pip install

pip install bluealpha-incrementality-mcp
bluealpha-incrementality-mcp

What you need

• uv — handles Python automatically, no separate Python install:

  curl -LsSf https://astral.sh/uv/install.sh | sh
  

• An MCP client — Claude Desktop, Claude Code, or any MCP-compatible client
• (Optional) A CSV with historical geo-level KPI data — if you want the data-driven feasibility checks. Columns for geography, time, and a numeric KPI.

Note: This MCP runs as a stdio subprocess on the user's local machine. CSV paths must point to files on the same machine as the MCP client — it cannot read files inside Claude.ai web sandboxes or Cowork environments. If you're working in Cowork, export/download the file locally first.

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The Happy Path

check_test_feasibility  →  capture_test_context  →  generate_test_plan  →  prepare_bluealpha_handoff
     (yes/no)               (business frame)         (handoff doc)          (email + booking link)

A marketer opens Claude and says "We spend $200k/month on Connected TV and I'm not sure it's working. Help me figure out what to do." Claude walks them through feasibility, asks about budget/goals/constraints, generates a plan, and produces an email draft + booking link for the BlueAlpha team — all in one conversation.

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Example Prompts

• "What is incrementality testing?"
• "How long should I run my test?"
• "I spend $300k/month on paid media. Is testing worth it?"
• "Here's my data at ~/Downloads/conversions.csv — can I even run tests?"
• "My CMO wants to cut Connected TV by 40%. Help me build a test to justify or push back."
• "We need to hit 2M subscribers by EoY. Which channel should I test first?"
• "Build me a testing roadmap for the next 6 months."
• "We can't pause California for legal reasons."
• "Write this up for BlueAlpha to pick up."

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Tools (14)

Education

Tool	What it does
explain_concept	Plain-language explainer for topics like geo lift, holdout, uplift, Causal Impact, statistical power, test duration, control selection. Matches natural-language queries.
list_available_concepts	Lists all topics that can be explained.

Feasibility

Tool	What it does
check_test_feasibility	High-level yes/no verdict from your CSV data. Five checks: data quality (duplicates, gaps, nulls), historical depth, geo diversity, volume per geo, inter-geo similarity. No stats jargon.
estimate_mmm_value	Quick sizing: "You spend $X → smarter allocation could save ~$Y/year."

Data profiling

Tool	What it does
profile_geo_data	Auto-detects geo/time/KPI columns in a CSV, returns schema and per-geo volume stats.
recommend_treatment_control_geos	Correlation-based split with volume balancing and similarity score.
calculate_power_from_data	Planning heuristic using actual observed volumes. Flagged as planning-only — real power analysis is done by your data science team.

Design & planning

Tool	What it does
design_test	Recommends test type (uplift vs holdout), geo counts, and duration from a business objective.
calculate_power	Manual power analysis from typed-in parameters.
calculate_sample_size	Sample size for user-level conversion lift tests (Meta / Google style).
estimate_budget	Media budget for an uplift test (CPM × impressions × geos × weeks).
plan_testing_calendar	Multi-quarter roadmap across channels, avoiding blackout periods (Black Friday, holidays).
capture_test_context	The core planning tool. Captures business question, growth target, budget, KPI, test objective, success definition, decision criteria, off-limits geos/periods, untouchable budgets, regulatory constraints, calendar conflicts, prior tests, stakeholders, priorities. Flags missing info so Claude can ask follow-ups.

Handoff

Tool	What it does
generate_test_plan	Full structured plan doc with business_context, execution plan, timeline, risks. Takes the output of capture_test_context.
prepare_bluealpha_handoff	Final step. Produces an email draft to the BlueAlpha team, a one-line Slack brief, and a pre-configured calendar booking link.

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Division of Labor

What this MCP does: Education, feasibility, planning, business context capture, handoff packaging.

What this MCP explicitly does NOT do: Final test design, synthetic control construction, real Causal Impact / BSTS modelling, post-test causal inference. Those are done by the BlueAlpha team (or your internal data scientists) using the handoff document produced by this tool.

This separation is deliberate. Marketers get a fast, accessible planning experience. Data scientists get clean, structured inputs. Nothing in this server pretends to be a substitute for rigorous statistical execution.

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Development

cd servers/incrementality
uv sync
uv run bluealpha-incrementality-mcp

About BlueAlpha

BlueAlpha runs production-grade incrementality tests and Marketing Mix Models for consumer brands. This planning tool is a free first step — when you're ready to execute, book a call or reach out to [e-mail].

License

MIT