
Startup Finance Metrics
io.github.MayankTalwar0Published by GitHub account MayankTalwar0v1.1.2Updated Oct 24, 2026
An MCP server for analyzing startup financial health and generating metrics reports locally.
The publisher's own server: Finance Foundation
Overview
A local MCP server that computes startup finance metrics such as runway, gross margin, CAC, LTV and Rule of 40, and renders Markdown and HTML reports.
- What you can do
- Compute startup financial metrics from structured inputs, including net burn, runway, gross margin, CAC, LTV, LTV:CAC, growth, churn, burn multiple, NRR, Rule of 40 and CAC payback
- Return insufficient_data with missing inputs instead of guessing when figures are absent or ambiguous
- Generate a unified Markdown and HTML report, either for one month or as a side-by-side comparison across several months
- Work from bank, Stripe or QBO/Xero CSV exports or pasted values, with the assistant categorizing transactions into revenue, COGS, S&M, payroll and G&A
- When to use it
- Useful for founders or operators who need a first-pass metrics pack for a fundraise, board meeting or investor update without an accountant, and who want the numbers computed on their own machine rather than in a cloud service.
- Requirements
- Runs locally over stdio via uvx from the PyPI package startup-finance-mcp; uv must be installed (it fetches Python dependencies itself). No accounts, API keys or environment variables are declared. Inputs are supplied as JSON arguments, and reports are written to an output directory.
Installation
In SourceWeft
- Open Startup Finance Metrics in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
Startup Finance Metrics (MCP Server)
An MCP (Model Context Protocol) server for analyzing startup financial health and generating metrics reports locally.
🔒 PRIVACY & SECURITY FIRST:
- Zero Cloud Risk: This tool runs 100% locally on your machine/server.
- No Data Sent Externally: Financial data is NEVER sent to any external API, cloud provider, or third-party service (including SlickBooks).
- No Data Storage: The server processes inputs in-memory and returns the metrics directly to the MCP client. No data is stored, cached, or logged.
- Strictly Read-Only: This server executes NO financial state changes. It is a strictly read-only mathematical engine.
- Strictly Local Processing: Safely integrates with Claude Desktop, Cursor, Glama, and other MCP clients while maintaining full data sovereignty over your sensitive financial inputs.
Why This Exists
If you're a startup founder raising funds or preparing for a board meeting, investors will ask you for metrics like MRR, burn rate, gross margin, LTV:CAC, and runway — often on short notice. Most founders either don't track these consistently, or spend hours pulling numbers from bank statements and spreadsheets before every fundraise.
This tool turns your raw bank statement (or Stripe/QBO export) into a structured financial metrics report in minutes, entirely on your own machine. No accountant required for a first pass. No sensitive data leaving your computer.
What It Does
- Ingests Data: Accepts bank CSVs, Stripe export CSVs, QBO/Xero export CSVs, or pasted values. (For best results, provide a minimum 3-month bank statement and active user stats. Sample files are available in the
test/folder). - AI Transaction Categorization: The AI classifies each bank transaction into revenue, COGS, S&M, payroll, or G&A based on the description. This step is AI-driven and can make mistakes — e.g. misclassifying a contractor payment as payroll vs. COGS, or missing an ambiguous line item. Always review the categorizations before sharing results with investors.
- Computes Key Metrics: Calculates Net Burn, Runway, Gross Margin, CAC, LTV, Rule of 40, and more — across one or multiple months in a single comparative report.
- Strict Validation: Returns
insufficient_datawithmissing_inputsinstead of hallucinating values. If data is missing or ambiguous, the engine tells you what's needed rather than guessing. - Generates Reports: Creates clean, formatted Markdown and HTML reports — one unified report covering all months supplied, with side-by-side period comparison.
mcp-name: io.github.MayankTalwar0/startup-finance-metrics
Setup & Installation
Option 1: Claude Desktop (Manual Installation for Non-Developers)
Since this tool runs entirely on your own machine to protect your financial data, it requires a one-time manual setup.
Good News: You do NOT need to have Python installed! The tool we use below (uv) will automatically download everything it needs invisibly in the background.
Step 1: Install uv
This server uses uv (a fast Python manager) to run locally. If you don't have it installed:
- Mac/Linux: Open your Terminal and run:
curl -LsSf https://astral.sh/uv/install.sh | sh - Windows: Open PowerShell and run:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Step 2: Open Claude's Configuration
- Open the Claude Desktop App.
- In the top left menu, click Claude -> Settings (or Preferences).
- Click on the Developer tab in the left sidebar.
- Click the Edit Config button. This will open a file named
claude_desktop_config.jsonin your default text editor.
Step 3: Add the Server
Replace the contents of that file with the following code (if you already have other servers, just add the startup-finance-metrics block inside your existing mcpServers):
Step 4: Restart Claude Save the file, close it, and completely restart Claude Desktop. You will now see a new "hammer" (Tools) icon in your Claude chats!
Option 2: Claude Code, Glama, or Custom Cursor setup
For CLI agents like Claude Code, or if you prefer to manually configure Glama and Cursor, use the uvx command:
For Claude Code:
For Glama / Cursor (Custom MCP config):
Option 3: Local Development
Available MCP Tools
This server provides the following tools to the MCP client:
computeFinancialMetrics(inputs_json: str): Computes startup financial metrics (runway, gross margin, CAC, LTV, etc.) from structured inputs. Called once per month when analyzing multi-month data.generateFinancialReport(metrics_json: str, output_dir: str): Renders a unified HTML + Markdown report. Accepts either a single-month payload or a multi-month{"months": [...]}payload — producing one comparative report across all periods supplied.
Using as a Standalone AI Skill
If you don't want to use the full MCP server and just want a simple prompt to use in tools like Claude Code or OpenClaw, you can find the raw skill prompt in skills/SKILL.md.
Metrics Reference
License
MIT
Built By SlickBooks
Built by Mayank, founder of SlickBooks. SlickBooks provides managed bookkeeping, bookkeeping automation, financial forecast automation, and custom finance agents.
Source: README.md at commit 69ab71c
Tools
0Version history
1- v1.1.2LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts
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