strategy-mcp is an open source MCP server that exposes professional-grade product strategy frameworks as structured tools. Any MCP-compatible AI assistant (Claude, Cursor, Cline) can install it and immediately get access to structured strategy analysis, RICE, JTBD, competitive positioning, assumption mapping, and more.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"strategy-mcp": {
"args": [
"run",
"--with",
"strategy-mcp",
"python",
"server.py"
],
"command": "uv"
}
}
}Are you the author?
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Professional-grade product strategy frameworks as MCP tools.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
uvx 'strategy-mcp' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
Five weighted categories — click any category to see the underlying evidence.
No known CVEs.
Checked strategy-mcp against OSV.dev.
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Professional-grade product strategy frameworks as MCP tools.
Give any MCP-compatible AI assistant — Claude Code, Cursor, Cline — instant access to 12 structured strategy frameworks. Not templates. Not prompts. Actual tools that accept your inputs, apply the framework, show the reasoning, and return specific next steps.
AI tools are great at generating content. They're inconsistent at applying structured thinking.
strategy-mcp is the product management layer that's been missing from the AI toolkit. Every framework a PM reaches for — RICE scoring, Jobs-to-be-Done, competitive positioning, OKR generation — encoded as a tool your AI can use natively.
Each tool returns:
Built by Sohaib Thiab — former CPO, now building AI products in public.
strategy-mcp is published on PyPI — install it with a single command.
claude mcp add strategy-mcp -- uv run --with strategy-mcp python server.py
Add to your Cursor MCP settings (.cursor/mcp.json):
{
"mcpServers": {
"strategy-mcp": {
"command": "uv",
"args": ["run", "--with", "strategy-mcp", "python", "server.py"]
}
}
}
Add to your Cline MCP settings:
{
"mcpServers": {
"strategy-mcp": {
"command": "uv",
"args": ["run", "--with", "strategy-mcp", "python", "server.py"]
}
}
}
pip install strategy-mcp
git clone https://github.com/sohaibt/strategy-mcp.git
cd strategy-mcp
uv run python server.py
| Tool | What it does |
|---|---|
rice_score | Score a feature using Reach, Impact, Confidence, Effort. Returns a calculated score, priority tier, and factor-by-factor analysis. |
| Tool | What it does |
|---|---|
assumption_map | Map assumptions into a 2x2 matrix of confidence vs. impact. Identifies your riskiest bets and what to test first. |
jobs_to_be_done | Analyze a feature through the JTBD lens — job statement, functional/emotional/social dimensions, hiring criteria, switching barriers. |
| Tool | What it does |
|---|---|
competitive_position | Map your product and competitors on a 2-axis chart. Identifies nearest threats, white space, and differentiation opportunities. |
| Tool | What it does |
|---|---|
business_model_review | Assess a business model using the Business Model Canvas. Reviews all 9 components for clarity, gaps, and coherence. |
tam_sam_som | Estimate addressable market tiers with top-down + bottom-up cross-validation. Includes sanity checks and key assumptions. |
pricing_strategy | Analyze pricing against positioning and the competitive landscape. Recommends a model, price range, and flags risks. |