MCP Server

The MCP (Model Context Protocol) server exposes all 60+ valuation functions as tools for AI agents. Connect with Claude Desktop, Cursor, OpenCode, or any MCP-compatible client.

Installation

pip install startup-valuation[mcp]

Quick Start (stdio mode)

cd mcp_server && python server.py

The server runs in stdio mode by default — it reads JSON-RPC from stdin and writes responses to stdout.

Connecting with Claude Desktop

1. Open Claude Desktop settings
2. Go to Developer → Edit Config
3. Add the MCP server to mcp.json:

{
  "mcpServers": {
    "startup-valuation": {
      "command": "python",
      "args": ["/path/to/startup-valuation/mcp_server/server.py"],
      "cwd": "/path/to/startup-valuation/mcp_server"
    }
  }
}

1. Restart Claude Desktop
2. Claude will now have access to all 60+ valuation tools

Connecting with Cursor

1. Open Cursor settings
2. Go to Features → MCP Servers
3. Add a new MCP server:

{
  "mcpServers": {
    "startup-valuation": {
      "command": "python",
      "args": ["/path/to/startup-valuation/mcp_server/server.py"],
      "cwd": "/path/to/startup-valuation/mcp_server"
    }
  }
}

1. Restart Cursor
2. Use @ to invoke valuation tools in chat

Connecting with OpenCode

Add to your opencode.json:

{
  "mcp": {
    "servers": {
      "startup-valuation": {
        "command": "python",
        "args": ["/path/to/startup-valuation/mcp_server/server.py"],
        "cwd": "/path/to/startup-valuation/mcp_server"
      }
    }
  }
}

SSE Transport (Remote Mode)

For remote access, use SSE transport instead of stdio:

# mcp_server/server.py — modify the run line:
if __name__ == "__main__":
    mcp.run(transport="sse", host="0.0.0.0", port=8000)

Then connect your client to http://your-server:8000/sse.

Tool Reference

Probability

Tool	Parameters	Returns
valuation_expected_value	outcomes: list[float], probabilities: list[float]	{"value": float, "method": str, "inputs": dict}
valuation_joint_probability	probabilities: list[float]	{"value": float, "method": str}
valuation_probability_weighted	probabilities: list[float], values: list[float]	{"value": float, "method": str}
valuation_portfolio_return	probabilities: list[float], returns: list[float]	{"value": float, "method": str}
valuation_expected_value_continuous	lower: float, upper: float	{"value": float, "method": str}

Time Value

Tool	Parameters	Returns
valuation_present_value	future_value: float, rate: float, periods: float	{"value": float, "method": str}
valuation_npv	cash_flows: list[float], rate: float	{"value": float, "method": str}

CAPM

Tool	Parameters	Returns
valuation_capm	risk_free_rate: float, beta: float, market_return: float	{"value": float, "method": str}
valuation_portfolio_beta	weights: list[float], betas: list[float]	{"value": float, "method": str}
valuation_startup_capm	risk_free_rate: float, beta: float, market_risk_premium: float, size_premium: float = 0, startup_premium: float = 0	{"value": float, "method": str}

Core Valuation

Tool	Parameters	Returns
valuation_scorecard	average_valuation: float, weights: list[float], scores: list[float]	{"value": float, "method": str}
valuation_berkus	sound_idea: float = 0, prototype: float = 0, quality_team: float = 0, strategic_relationships: float = 0, product_rollout: float = 0	{"value": float, "method": str}
valuation_risk_factor_summation	base_valuation: float, risk_ratings: list[float]	{"value": float, "method": str}
valuation_vc_post_money	terminal_value: float, target_return: float	{"value": float, "method": str}
valuation_vc_pre_money	post_money: float, investment: float	{"value": float, "method": str}

Advanced

Tool	Parameters	Returns
valuation_black_scholes	underlying: float, strike: float, risk_free_rate: float, volatility: float, time_to_maturity: float	{"value": float, "method": str}
valuation_scenario_analysis	scenarios: list[dict] — each dict: {name: str, probability: float, value: float}	{"value": float, "method": str}
valuation_binomial	underlying: float, strike: float, risk_free_rate: float, volatility: float, time_to_maturity: float, steps: int = 50	{"value": float, "method": str}

SaaS

Tool	Parameters	Returns
valuation_saas_ltv	arpu: float, gross_margin: float, churn_rate: float	{"value": float, "method": str}
valuation_rule_of_40	growth_rate: float, profit_margin: float	{"value": float, "method": str}
valuation_saas_multiple	arr: float, multiple: float	{"value": float, "method": str}

Biotech

Tool	Parameters	Returns
valuation_decision_tree	probabilities: list[float], terminal_value: float	{"value": float, "method": str}
valuation_peak_sales	patient_population: float, penetration: float, price: float, compliance: float = 1.0	{"value": float, "method": str}
valuation_pipeline	drugs: list[dict], discount_rate: float	{"value": float, "method": str}

Fintech

Tool	Parameters	Returns
valuation_payment_revenue	transaction_volume: float, take_rate: float	{"value": float, "method": str}
valuation_lending	loan_book: float, roe: float, pe_multiple: float, npl_reserves: float = 0	{"value": float, "method": str}
valuation_payment_processor	transaction_volume: float, take_rate: float, growth_rate: float, discount_rate: float, terminal_multiple: float, years: int = 5	{"value": float, "method": str}
valuation_neobank	customers: int, arpu: float, gross_margin: float, churn_rate: float, pe_multiple: float	{"value": float, "method": str}

Marketplace

Tool	Parameters	Returns
valuation_take_rate	revenue: float, gmv: float	{"value": float, "method": str}
valuation_gmv_multiple	gmv: float, multiple: float	{"value": float, "method": str}
valuation_buyer_retention	buyers_period_1: int, buyers_repeat: int	{"value": float, "method": str}
valuation_network_density	active_buyers: int, active_sellers: int, total_users: int	{"value": float, "method": str}

Hardware

Tool	Parameters	Returns
valuation_trl	market_size: float, market_share: float, margin: float, multiple: float, trl_discount: float	{"value": float, "method": str}

International

Tool	Parameters	Returns
valuation_ppp	spot_rate: float, inflation_foreign: float, inflation_domestic: float	{"value": float, "method": str}
valuation_crp	sovereign_yield: float, us_treasury_yield: float	{"value": float, "method": str}
valuation_intl_capm	risk_free_rate: float, beta: float, mrp: float, crp: float	{"value": float, "method": str}

Stakeholders

Tool	Parameters	Returns
valuation_dilution	ownership_before: float, investment: float, post_money: float	{"value": float, "method": str}
valuation_opm	enterprise_value: float, liquidation_pref: float, time_to_exit: float, volatility: float	{"value": float, "method": str}
valuation_pwerm	scenarios: list[dict]	{"value": float, "method": str}
valuation_liquidation	assets: dict, recovery_rates: dict	{"value": float, "method": str}
valuation_risk_adjusted_synergy	revenue_synergies: float, cost_synergies: float, prob_revenue: float = 0.4, prob_cost: float = 0.8, discount_rate: float = 0.10, years: int = 3	{"value": float, "method": str}
valuation_intrinsic_option	strike_price: float, fair_market_value: float, shares: int	{"value": float, "method": str}
valuation_employee_option	scenarios: list[dict]	{"value": float, "method": str}
valuation_vesting_adjusted	total_value: float, vested_fraction: float, annual_vest_rate: float = 0.25, retention_prob: float = 0.8, years_remaining: int = 3	{"value": float, "method": str}
valuation_cash_equity_breakeven	salary_reduction: float, equity_value: float, tax_rate: float = 0.30, discount_rate: float = 0.20, years: int = 4	{"value": float, "method": str}
valuation_max_asset_loan	cash: float = 0, accounts_receivable: float = 0, inventory: float = 0, equipment: float = 0, real_estate: float = 0	{"value": float, "method": str}

Emerging

Tool	Parameters	Returns
valuation_safe_discount	series_a_price: float, discount: float	{"value": float, "method": str}
valuation_safe_cap	cap: float, series_a_price: float	{"value": float, "method": str}
valuation_safe_expected	investment: float, cap: float, discount: float, series_a_valuation: float, series_a_price: float	{"value": float, "method": str}
valuation_token_value	transaction_volume: float, price_per_tx: float, velocity: float, supply: float	{"value": float, "method": str}
valuation_nvt_ratio	market_cap: float, daily_transaction_volume: float	{"value": float, "method": str}
valuation_esg_rate	base_rate: float, risk_premium: float = 0, opp_discount: float = 0	{"value": float, "method": str}
valuation_esg_premium	base_valuation: float, esg_score: float, premium_per_point: float = 0.02	{"value": float, "method": str}
valuation_esg_discount	base_valuation: float, esg_risk_score: float, discount_per_point: float = 0.01	{"value": float, "method": str}
valuation_metcalfes	n: float, k: float = 1.0	{"value": float, "method": str}
valuation_data_moat	data_volume: float, data_uniqueness: float, monetization_rate: float, competitive_advantage_years: float, discount_rate: float = 0.15	{"value": float, "method": str}
valuation_remote_npv	annual_savings: float, discount_rate: float	{"value": float, "method": str}
valuation_remote_premium	base_valuation: float, cost_savings_pct: float = 0.20, talent_access_premium: float = 0.10, productivity_gain: float = 0.05	{"value": float, "method": str}

Compound Tool

Tool	Parameters	Returns
valuation_full_analysis	average_valuation: float, weights: list[float], scores: list[float], terminal_value: float, target_return: float, investment: float	{"scorecard": dict, "vc_post_money": dict, "vc_pre_money": dict, "triangulated_mean": float}

Example: Using a Tool

Ask Claude: "Use the valuation_scorecard tool with average valuation of $1.5M, weights [0.30, 0.25, 0.15, 0.10, 0.10, 0.05, 0.05], and scores [1.25, 1.50, 1.20, 0.75, 1.00, 0.90, 1.00]"

Claude will call the tool and return:

{
  "value": 1800000.0,
  "method": "Scorecard Method"
}