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Nifra

The AI-native TypeScript framework. Typed APIs and full-stack SSR on five UI libraries, one app across Bun, Node, Deno, and the edge - built so both humans and coding agents can change it safely.

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Nifra is for software that is built, operated, and used with agents in the loop.

An agent should not be a chat bubble bolted onto an app, or a coding assistant guessing at an API. It should discover the real contract, call typed capabilities, stream progress into the UI, ask for approval at the right boundary, update state optimistically, reconcile with the server, and leave evidence that the work actually happened. Nifra makes that one system:

• Build surface: typed APIs, runtime schemas, a no-codegen client, full-stack SSR, and one app across five UI libraries and five runtimes.
• Agent surface: page-local WebMCP, remote MCP/MCP Apps, A2A, and AG-UI from the same capability and tool contracts.
• Execution surface: bounded agent turns, budgets, approvals, idempotency, cancellation, resumable evidence, and provider-neutral model ports.
• UI surface: deterministic predictive UI, shared run state, streamed deltas, human-in-the-loop decisions, content-free browser views, and Run Studio.
• Proof surface: live MCP project context plus typecheck, route assurance, effect provenance, manifests, and contract-derived verification gates.

One contract. Every surface.

The central design decision is simple: define the capability once, then project it to the surface that fits the moment. A page-local agent can use WebMCP while the page is open; a background agent can use remote MCP; another agent can use A2A; a human-facing client can consume AG-UI. They still meet the same typed validation, authorization, approval, output, and evidence boundary.

import { t } from "@nifrajs/schema"
import { defineAgentCapability, registerWebMcpTools } from "@nifrajs/webmcp"

export const addToCart = defineAgentCapability({
  name: "cart.add",
  description: "Add a product to the current cart.",
  input: t.object({ sku: t.string(), quantity: t.number() }),
  output: t.object({ cartVersion: t.string() }),
  writes: ["cart"],
  execute: (input) => addItemOnTheServer(input),
  predict: ({ input, version }) => ({
    baseVersion: version,
    patch: [{ op: "add", path: "/items/-", value: input }],
  }),
})

// Explicit page-local discovery. Unsupported hosts receive a safe no-op report.
await registerWebMcpTools([addToCart])

The same addToCart.tool can be projected into Nifra's remote MCP adapter or called by an agent runner. Predictions are deterministic application code—not LLM guesses—and commit, rollback, conflict, expiry, and authoritative reconciliation are explicit outcomes.

See the WebMCP and predictive UI guide and the agent layer.

Shortened. The full README is on GitHub.