Build with an LLM

Give coding agents grounded Zama SDK context — install the Zama skills, or point agents without skill support at the SDK's llms.txt files.

Give your coding agent a grounded view of the Zama SDK so it writes correct FHEVM code instead of guessing. The fastest way is to install the Zama skills; otherwise point your agent at the SDK's llms.txt files or connect the docs over MCP.

Install the Zama skills

The Zama skills give your agent expert, always-current guidance on the protocol and SDK. They live in zama-ai/skills (separate from this repo) and install as one bundle of three skills that route automatically by what you're working on:

1. zama-typescript — the TypeScript SDK, React, browser, and Node.js integration. This is the skill that drives SDK work.

2. zama-solidity — encrypted Solidity, FHE types, ACL, and ERC-7984.

3. zama-protocol — FHEVM concepts, protocol architecture, and planning.

Install once and your agent has all three; ask an SDK question and zama-typescript loads automatically.

Claude Code

/plugin marketplace add zama-ai/skills
/plugin install zama-protocol@zama-skills

Other agents (npx)

For Codex, Cursor, or manual setup, see the skills README.

No skill support? Point your agent at the llms.txt files below instead.

Give guidance to AI agents / LLMs

The Zama SDK ships as @zama-fhe/sdk (and @zama-fhe/react-sdk for React) — not the legacy @zama-fhe/relayer-sdk that most LLM training data still defaults to. Point your agent at the SDK's LLM-ready files to ground it on the current API when it can't use skills — or to pull a specific doc on demand. They give a grounded map of the public docs, approved examples, and SDK reference without cloning the repo.

File	Use it when	Your agent gets
llms.txt	the agent needs to discover the right guide, example, or reference, then fetch only that	a compact map of guides, concepts, SDK and React reference pages, and approved examples
llms-full.txt	the agent has a large context window and you want the whole public corpus in one paste	the complete docs bundle plus approved examples and README context (API reports excluded)

Start with llms.txt for normal coding tasks; reach for llms-full.txt only when you want everything loaded at once. The source_path values such as docs/gitbook/src/... are provenance metadata, not local paths — if you haven't cloned the repo, use the raw GitHub URLs.

Example prompts

To ground an agent, paste:

You're building with the Zama SDK — @zama-fhe/sdk (and @zama-fhe/react-sdk for React), not the legacy @zama-fhe/relayer-sdk. Read https://raw.githubusercontent.com/zama-ai/sdk/main/llms.txt and follow its links to the relevant guides and approved examples before writing any code. Treat the official docs as the source of truth, prefer the official examples listed in llms.txt over ad hoc implementations, and use the API reference only to confirm exact signatures.

Then give it a task. (With the skills installed your agent is already grounded — skip straight here.)

React (wagmi)

Read https://raw.githubusercontent.com/zama-ai/sdk/main/llms.txt and follow its links to the relevant Zama SDK guides and approved examples before writing any code.

Add confidential balances and transfers to this Next.js app, following the approved react-wagmi example.

Node.js

Debugging

Connect the docs over MCP

Every page in these docs has a Copy ▾ menu (top-right) with built-in agent connectors — reach for these when you want live access to the current docs rather than a static paste:

• Connect with MCP — add the docs as an MCP server in Claude Code, Cursor, VS Code, or Codex for live, searchable access to the current API. Stronger than llms.txt for MCP-capable agents, since it always reflects the published docs.

• Open in ChatGPT / Open in Claude — start a chat already grounded on the page you're viewing.

• Copy page as Markdown / View as Markdown — grab a single page as plain markdown for your agent, or append .md to any docs URL (e.g. https://docs.zama.org/protocol/sdk/overview.md).