k-phi
OfficialAllows ChatGPT to analyze financial data (e.g., CSV exports of ledgers) using K-Phi's financial analysis engine, covering ratios, DSCR, treasury, covenants, FEC, and balance diagnostics.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@k-phiAnalyze this GL export for DSCR and cash flow."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
K-Phi — public MCP server (skeleton)
MCP server (Streamable HTTP, stateless) exposing K-Phi analysis to AI assistants (Claude, ChatGPT, Cursor, Copilot…). Anonymous rate-limited access, signed upload for large files, deep link to K-Phi for conversion.
See kphi-mcp-public-spec.md for the full spec.
Run
npm install
npm run dev # compile + démarre sur :3000
curl localhost:3000/healthzEnvironment variables:
Var | Default | Role |
| 3000 | |
| base for | |
| base for signed upload links | |
| mcp | attribution |
Related MCP server: Analytics MCP
Test in Claude Desktop (before listing)
Add to claude_desktop_config.json (or via Settings → Connectors → Add custom connector with the public URL):
{
"mcpServers": {
"k-phi": {
"command": "npx",
"args": ["-y", "mcp-remote", "http://localhost:3000/mcp"]
}
}
}Then in Claude: "Here is my general ledger export, can you analyze this for me?" while pasting
a CSV. Verify that kphi_analyze_ledger is called. Then test ~20 phrasings
(ratios, DSCR, cash flow, covenants, FEC, balance sheet, "financial diagnostic"…) and adjust
the tool description in src/tools.ts until routing is reliable.
Structure
src/
server.ts endpoint /mcp (stateless), /upload/:token, /healthz
tools.ts les 4 outils + descriptions (= le pitch lu par le modèle)
engine.ts interface AnalysisEngine + MockEngine
store.ts interface Store + MemoryStore
ratelimit.ts session anonyme + quotasConnect to K-Phi (the 4 TODOs)
engine.ts— implementAnalysisEnginewith your existing engine (analyzefor inline CSV,analyzeFromStoragefor uploaded files).store.ts— replaceMemoryStorewith Postgres (dedicatedmcp_publicschema, 30-day purge); upload tokens in database or Redis.server.ts/upload/:token— replace with a pre-signed S3/R2 URL + antivirus, and trigger analysis on event rather than inline.ratelimit.ts— quotas in Redis; add OAuth 2.1 (Bearer) verification wired to your existing auth to lift quotas for accounts.
On the K-Phi application side: /a/:analysis_id route that creates an account via magic link and
attaches the analysis (this is the conversion point), and /r/:analysis_id route in read-only
shareable mode.
Listing
Usual directory prerequisites: public HTTPS URL, OAuth 2.1 or documented anonymous access, privacy policy, support contact, description and icon. Check current criteria: https://docs.claude.com and https://support.claude.com (Claude), OpenAI documentation for ChatGPT, registry.modelcontextprotocol.io.
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