MCP plugin for the AI-native spreadsheet

Connect your AI agent
to a spreadsheet it can’t break.

Layerz is an MCP server your Claude agent calls natively. Read model structure, update assumptions, compute projections, export Excel, without re-explaining context every session. Named references, so the formulas hold when the agent touches them.

Connect your agent - free Prefer the REST API

MCP-compatible · BYOA · Export to standard .xlsx

The problem with AI + finance today

Claude is powerful — the layer underneath isn't.

You use Claude. You build financial analyses in chat. The next session, you start over.

There's no persistent model structure your agent can navigate. You paste numbers, re-explain assumptions, rebuild context.

What the MCP plugin gives your agent

A model your agent can actually navigate.

Your agent navigates the model. You review the outputs. The structure persists across sessions.

Read model structure

Variable names, types, formulas, dependencies.

Query computed values

Revenue, EBITDA, cash flow, any output at any period.

Update assumptions

Change a growth rate or headcount number, all outputs recompute automatically.

Export Excel

Trigger a clean .xlsx from your agent session.

BYOA — Bring your own agent

Your prompts, your data, your environment.

Layerz does not capture your Claude session. Connect your own Claude Max subscription or API key. Layerz is the structured backend, not the middleware.

Supported: Claude (MCP), any MCP-compatible agent, Claude Code.

How to connect

Three steps to a connected agent.

Add to Claude in one click

Opens claude.ai with the Layerz connector pre-filled. You confirm, sign in, done. Or set it up manually below.

Add the Layerz MCP server

Add the connector to your Claude configuration.

Authenticate

Call layerz_* tools

Your agent now has access to layerz_read, layerz_update_branch, layerz_get_model and more.

→ Full MCP reference and llms.txt

MCP clients

Install once in your agent of choice.

Client	Auth	Install
Claude	OAuth	Settings → Connectors → Add custom connector
Claude Cowork	OAuth	claude.ai → Settings → Connectors → Add custom connector
Claude Code	OAuth	claude mcp add -t http layerz https://layerz.cc/mcp
ChatGPT	OAuth	Settings → Apps & Connectors → Add new connector
OpenAI Codex	OAuth	codex mcp add layerz --url https://layerz.cc/mcp
Mistral Le Chat	OAuth	Settings → Connectors → Add custom MCP connector
OpenCode	OAuth	opencode.json: {"mcp":{"layerz":{"type":"remote","url":"https://layerz.cc/mcp","oauth":{}}}} then: opencode mcp auth layerz

Full install guide on GitHub

What you can build

From prompt to model to .xlsx.

Auto-populated budget models

Your agent fills a model structure from a prompt — assumptions first, then projections. Change one variable, all outputs update. No re-run.

Persistent unit economics

Define CAC, LTV, payback period once. Query across Claude sessions without rebuilding context.

Multi-scenario analysis

Run base / upside / downside on a shared model structure. Export any scenario to .xlsx — your colleagues get a clean file, they never see the agent.

Example prompts

Say it in plain English. Your agent does the modeling.

“Show me the revenue assumptions in my latest Layerz model and explain how they drive EBITDA.”

layerz_list_modelslayerz_read

“Raise the churn assumption to 2.5% from March and show me the impact on year-end cash.”

layerz_patchlayerz_read

“Create an upside scenario with 20% faster hiring, compare it to base, then export it to Excel.”

layerz_update_branchlayerz_export

Questions, or stuck on setup? Write to [email protected].

Build the structure once. Query it from every session.

Connect your agent - free