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High-precision finance & business calculations for AI agents — exact decimals, never floats.
About
High-precision finance & business calculations for AI agents — exact decimals, never floats.
Remote endpoints: streamable-http: https://precisioncalc-mcp.pages.dev/mcp
Security Report
PrecisionCalc MCP is a well-architected financial calculation server with proper authentication, rate limiting, and input validation. Code quality is high with comprehensive error handling and no malicious patterns detected. Minor concerns around async error handling in the Worker build and env var exposure in error messages do not significantly impact security given the server's purpose and safeguards. Supply chain analysis found 7 known vulnerabilities in dependencies (0 critical, 6 high severity).
4 files analyzed · 11 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
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How to Install & Connect
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
Documentation
View on GitHubFrom the project's GitHub README.
PrecisionCalc MCP
A deterministic Model Context Protocol (MCP) server that gives LLM agents reliable, high-precision business, finance, and operational calculations.
LLMs routinely lose precision or hallucinate on multi-step financial formulas,
currency conversions, business-day logic, and growth math. PrecisionCalc offloads
that work to exact, transparent tools. Every monetary/financial value is computed
with Python's decimal module (never floats), and every result is returned in
a consistent, agent-parseable JSON envelope that includes the exact value, a
human-readable value, the formula applied, the inputs used, the unit, and
any assumptions/warnings.
v2 highlights: live + historical FX (ECB), 14 SaaS metrics, NPV/IRR, loan amortization, depreciation, a
batch_calculatetool, per-country holidays, API-key auth + rate limiting + usage metering on the HTTP transport, structured JSON logging, optional OpenTelemetry tracing, and property-based tests.
🌐 Live hosted server (free, no install)
A public remote MCP server runs on Cloudflare's edge — point any Streamable-HTTP MCP client at it:
https://precisioncalc-mcp.pages.dev/mcp
{ "mcpServers": { "precisioncalc": {
"type": "http", "url": "https://precisioncalc-mcp.pages.dev/mcp" } } }
The edge build (worker-src/) is a Cloudflare Pages Function that mirrors the
Python engine using decimal.js — verified 17/17 exact output parity. Landing
page + docs: https://precisioncalc-mcp.pages.dev.
Plans (hosted endpoint)
| Plan | Price | Daily calls | Live/historical FX | batch_calculate |
|---|---|---|---|---|
| Free (no key) | $0 | 15 / day (per IP) | ❌ static only | ❌ |
| Starter | $12/mo | 5,000 / day | ✅ | ✅ |
| Pro | $39/mo | 50,000 / day | ✅ | ✅ |
Checkout is Stripe (subscription). On success you get an API key instantly; send it as
X-API-Key: <key> (or Authorization: Bearer <key>). Manage/cancel at /portal.
When a limit is hit, tools return a structured status:"error" envelope with type,
usage, and an upgrade block containing checkout URLs — so an agent can surface the
paywall to the user and act on it. Self-host (below) for unlimited calls with your own keys.
Billing internals live in worker-src/billing.mjs (Stripe REST + Cloudflare KV for keys
and daily counters). Server env: STRIPE_SECRET_KEY, STRIPE_WEBHOOK_SECRET,
PRICE_STARTER, PRICE_PRO, FREE_DAILY, STARTER_DAILY, PRO_DAILY, and a
PRECISIONCALC_KV namespace binding (see wrangler.toml).
Rebuild/redeploy the edge server:
npm install # decimal.js + esbuild
npm run deploy # bundles worker-src -> site/_worker.js and deploys to Pages
What it does
11 tools, all returning a uniform structured response:
| Tool | Purpose |
|---|---|
calculate_metric | 14 SaaS/business metrics (LTV, CAC, churn, MRR growth, NRR, GRR, Rule of 40, magic number, break-even, ...) |
currency_convert | Convert 9 major currencies; static (offline) or live/historical ECB rates |
business_days | Add/count business days, next/previous; US/UK/EU + any ISO country + custom holidays |
compound_growth | Future value, present value, CAGR; 7 compounding frequencies incl. continuous |
net_present_value | NPV / discounted cash flow of a cashflow series |
internal_rate_of_return | IRR (Newton + bisection fallback) |
loan_amortization | Level-payment loan: payment, totals, full schedule, extra-payment payoff |
depreciation | straight-line / declining-balance / sum-of-years-digits schedules |
batch_calculate | Run many calculations in one request |
list_metrics | Discovery: every metric with descriptions + required params |
health_check | Server status, version, capabilities |
Consistent response envelope
Success:
{
"status": "success",
"value": "1600", // exact, full-precision (string for money/rates)
"formatted_value": "$1,600.00", // human-readable
"formula": "LTV = (ARPU * gross_margin) / churn_rate",
"inputs_used": { "arpu": "100", "gross_margin": "0.8", "churn_rate": "0.05" },
"unit": "USD",
"notes": ["LTV = (ARPU x gross_margin) / churn_rate.", "..."]
}
Error (never raised across the tool boundary):
{
"status": "error",
"error": {
"type": "missing_parameter",
"message": "Missing required parameter 'churn_rate'.",
"hint": "Include 'churn_rate' in params. See list_metrics for the full schema."
}
}
Project structure
precisioncalc-mcp/
├── server.py # MCP server: tool definitions + transports
├── security.py # API-key auth + token-bucket rate limit + metering (ASGI)
├── observability.py # Structured JSON logging + optional OpenTelemetry
├── requirements.txt / pyproject.toml
├── Dockerfile / .dockerignore
├── fly.toml / render.yaml # One-click hosting configs
├── .env.example
├── calculations/
│ ├── _util.py # Decimal coercion, validation, formatting
│ ├── metrics.py # 14 business/SaaS metrics + catalog
│ ├── currency.py # FX: static + Frankfurter (live/historical) providers
│ ├── business_days.py # Region-aware holidays (built-in + `holidays` lib)
│ ├── growth.py # FV / PV / CAGR
│ └── finance.py # NPV / IRR / loan amortization / depreciation
├── schemas/responses.py # Response envelope helpers
├── examples/agent_example.py # End-to-end MCP client demo
├── site/ # Static landing/docs page (Cloudflare Pages)
└── tests/ # 49 unit tests + Hypothesis property tests
Requirements
- Python 3.11+ (developed/tested on 3.12)
- Core:
mcp,python-dateutil - Recommended:
uvicorn+starlette(HTTP transport),holidays(per-country calendars) - Optional:
opentelemetry-sdk(tracing),pytest+hypothesis(tests)
The server auto-detects the SDK layout and works with mcp >= 2.0
(MCPServer), mcp 1.x (FastMCP), or the standalone fastmcp package.
Run it locally
cd precisioncalc-mcp
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt # or: pip install -e ".[all]"
# stdio transport (default; how MCP clients launch it)
python server.py # or: precisioncalc-mcp (console entrypoint)
# Streamable HTTP transport (endpoint: /mcp)
python server.py http
PRECISIONCALC_API_KEYS=key1,key2 PRECISIONCALC_FX_PROVIDER=frankfurter python server.py http
Demo + tests:
python examples/agent_example.py # live end-to-end over stdio
python tests/test_calculations.py # 28 core tests (no pytest needed)
python tests/test_v2.py # 17 v2 tests
python tests/test_properties.py # Hypothesis property tests
# or simply: pytest -q
Register with an MCP client (stdio)
{ "mcpServers": { "precisioncalc": {
"command": "python", "args": ["/absolute/path/to/precisioncalc-mcp/server.py"] } } }
Deploy
Docker
docker build -t precisioncalc-mcp .
docker run --rm -p 8000:8000 -e PRECISIONCALC_API_KEYS=your-key precisioncalc-mcp
docker run --rm -i precisioncalc-mcp python server.py stdio
Fly.io
fly launch --no-deploy
fly secrets set PRECISIONCALC_API_KEYS=key1,key2
fly deploy
Render.com
Push to GitHub, then New + → Blueprint and point at the repo (render.yaml).
Set PRECISIONCALC_API_KEYS as a secret in the dashboard.
Configuration (env vars)
| Var | Default | Purpose |
|---|---|---|
PRECISIONCALC_HOST / PRECISIONCALC_PORT | 127.0.0.1 / 8000 | HTTP bind |
PRECISIONCALC_API_KEYS | (empty) | Comma-separated keys. Empty = open mode (still metered/limited by IP) |
PRECISIONCALC_RATE_LIMIT_PER_MIN / _BURST | 120 / 40 | Token-bucket limits |
PRECISIONCALC_METRICS_PATH | /metrics | Usage-metrics endpoint |
PRECISIONCALC_FX_PROVIDER | static | static or frankfurter (live/historical ECB) |
PRECISIONCALC_FX_TTL / _TIMEOUT | 3600 / 4 | FX cache TTL / HTTP timeout (s) |
PRECISIONCALC_LOG_LEVEL / _LOG_JSON | INFO / 1 | Logging |
PRECISIONCALC_OTEL | 0 | 1 enables OpenTelemetry tracing if SDK present |
Tools & parameters
calculate_metric(metric, params, currency="USD")
Rates/margins are decimals (0.05 = 5%).
| metric | params | unit |
|---|---|---|
ltv | arpu, churn_rate, gross_margin(=1) | currency |
cac | total_spend, new_customers | currency |
ltv_cac_ratio | ltv, cac | ratio |
payback_period_months | cac, monthly_revenue_per_customer, gross_margin(=1) | months |
contribution_margin | revenue, variable_costs | currency |
gross_margin | revenue, cogs | percent |
churn_rate | customers_lost, customers_at_start | percent |
mrr_growth_rate | beginning_mrr, ending_mrr | percent |
arr | mrr | currency |
break_even_units | fixed_costs, price_per_unit, variable_cost_per_unit | units |
nrr | starting_mrr, expansion_mrr, contraction_mrr, churned_mrr | percent |
grr | starting_mrr, contraction_mrr, churned_mrr | percent |
rule_of_40 | growth_rate, profit_margin | percent |
magic_number | current_quarter_revenue, prior_quarter_revenue, prior_quarter_sm_spend | ratio |
currency_convert(amount, from_currency, to_currency, date=None, live=None)
USD, EUR, GBP, JPY, CAD, AUD, CHF, CNY, INR. date (YYYY-MM-DD) or live=true
uses live/historical ECB rates (frankfurter.app), with automatic static fallback
on any network failure. Returns rate, provider, is_live, and timestamps.
business_days(operation, start_date, days=None, end_date=None, region="US", custom_holidays=None)
operation: add_business_days | count_business_days (inclusive) | next_business_day |
previous_business_day. region: US | UK | EU | NONE, or any ISO country code
when the holidays package is installed (DE, FR, CA, AU, JP, IN, ...).
compound_growth(operation, rate, years, present_value, future_value, begin_value, end_value, compounding="annually", currency="USD")
operation: future_value | present_value | cagr.
compounding: daily | weekly | monthly | quarterly | semiannually | annually | continuous.
net_present_value(rate, cashflows, currency="USD")
NPV = Σ CFₜ/(1+rate)ᵗ. cashflows[0] = period 0 (usually the negative outlay).
internal_rate_of_return(cashflows, guess=0.1)
Per-period rate where NPV = 0. Requires a sign change in the cashflows.
loan_amortization(principal, annual_rate, term_months, extra_payment=0, currency="USD", include_schedule=false)
Returns monthly payment, months-to-payoff, total interest, total paid, and (optionally) the full month-by-month schedule.
depreciation(method, cost, salvage_value, useful_life_years, currency="USD")
method: straight_line | declining_balance | sum_of_years_digits. Returns the
full yearly schedule; book value converges to salvage_value.
batch_calculate(calls)
calls: list of {"tool": <name>, "arguments": {...}} (max 100). One item failing never
aborts the batch.
list_metrics() / health_check()
Discovery + status. No parameters.
Example MCP tool-call payloads
{ "name": "calculate_metric",
"arguments": { "metric": "rule_of_40", "params": { "growth_rate": 0.30, "profit_margin": 0.15 } } }
{ "name": "currency_convert",
"arguments": { "amount": 5000, "from_currency": "EUR", "to_currency": "GBP", "date": "2024-01-15" } }
{ "name": "net_present_value",
"arguments": { "rate": 0.10, "cashflows": [-10000, 3000, 4200, 6800] } }
{ "name": "loan_amortization",
"arguments": { "principal": 250000, "annual_rate": 0.065, "term_months": 360, "include_schedule": false } }
{ "name": "batch_calculate",
"arguments": { "calls": [
{ "tool": "internal_rate_of_return", "arguments": { "cashflows": [-10000, 3000, 4200, 6800] } },
{ "tool": "depreciation", "arguments": { "method": "declining_balance", "cost": 50000, "salvage_value": 5000, "useful_life_years": 5 } }
] } }
Design decisions & assumptions
- Decimal everywhere money/rates matter;
valueis serialized as a string to prevent float loss in JSON, with a separate prettyformatted_value. Precision = 50 sig figs. - Rates/margins are decimals (
0.05= 5%), documented in every tool. - FX:
staticUSD-based table (as_of2024-06-01) is the offline default;frankfurterprovider adds live + historical ECB rates with in-memory TTL cache and graceful static fallback. - Business days: holidays computed per-year (floating US, Easter-based UK/EU);
countis inclusive;addaccepts negatives; custom holidays unioned; any ISO country viaholidayslib. - IRR uses Newton's method with a bracketed bisection fallback; requires a sign change.
- Errors never cross the tool boundary as exceptions — always
status:"error"with a machinetype+ actionablehint. - HTTP hardening is opt-in via env: API keys, token-bucket rate limiting,
/metricsusage. - SDK compatibility shim runs on
mcp>=2.0,mcp 1.x, or standalonefastmcpunchanged.
Monetization hooks
- Auth —
PRECISIONCALC_API_KEYS; requests needX-API-KeyorAuthorization: Bearer. - Rate limiting — per-key token bucket (per-IP in open mode); swap for Redis to scale.
- Usage metering — in-memory counters exposed at
/metrics; the seam for per-key billing. - FX provider —
calculations/currency.py::RateProvideris the drop-in point for a licensed feed.
Roadmap (post-v2)
- Redis-backed rate limiting + billing-grade usage metering.
- Persisted historical FX + more providers; multi-currency carry through metrics.
- Bond pricing/yield, WACC, options (Black-Scholes), tax/VAT, unit conversions.
- Prometheus exporter + Grafana dashboard alongside OTel traces.
- Published PyPI package + Docker image on GHCR; hosted multi-tenant SaaS.
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