Hyperlambda GitHub
For AI Agent Builders

Build AI Agents That Can Create Their Own Backend Tools

Hyperlambda compiles natural language into deterministic ASTs, allowing agents to generate APIs, workflows, and backend functions safely inside a constrained runtime.

Try the AST Playground See How It Works
600,000+ training snippets behind the Hyperlambda Generator
Every generated slot is verified against your cloudlet — hallucinated invocations cannot compile
MIT-licensed and self-hosted — your agents, your hardware
The problem

Most agents can think. Few can safely act.

AI agents are compelling until they need real backend leverage. Planning is easy. Generating reliable tools, APIs, workflows, and data operations is where most stacks become fragile.

Traditional code generation creates text first and depends on validation later. That leaves agent builders with brittle outputs, unclear security boundaries, and execution paths that are hard to trust in production.

A Magic cloudlet connected to an AI agent, exposing 220 endpoints as callable tools with per-tool permissions
How Hyperlambda helps

A safer execution model for evolving agents

Hyperlambda is a natural language AST compiler. Instead of generating unrestricted Python or JavaScript, it compiles requests into strict executable structures that run inside a constrained C# runtime. And with the MCP plugin installed, your cloudlet hands every endpoint to any MCP-capable harness — Claude, Claude Code, Cursor, Codex — as callable tools, so the capabilities your agent generates become tools it can immediately invoke.

Deterministic execution

If it compiles, it runs as executable structure instead of loosely validated source text.

Runtime whitelisting

Generated nodes can only bind to capabilities explicitly allowed in the current runtime.

Fast backend generation

Agents can generate working APIs, workflows, and utilities in seconds as needs change.

The roles table that every generated endpoint is gated on
Why it matters

Controlled action beats unrestricted codegen

If you are building agents, the real challenge is not reasoning alone. It is controlled action. Your agents need to create tools, adapt to new tasks, and interact with real systems without turning execution into a trust problem.

Hyperlambda closes that gap by combining natural language compilation, deterministic execution, runtime safety, and on-demand backend generation in one model.

“Kudos for the incredible work: it's the first real IDE dedicated to AI.”
Samuele Contardi Samuele Contardi Software Architect
Use cases

What your agents can generate

APIs

Endpoints on demand

Let an agent create backend endpoints for specific workflows, entities, and operational tasks.

Workflows

Task specific logic

Generate backend flows for actions, automations, and multi-step operational behavior.

Data tools

Controlled database access

Create functions for querying, transforming, or updating data inside constrained runtime rules.

Utilities

Agent specific helpers

Extend your agents with tools built for the exact problem they need to solve right now.

UI

Widgets and interfaces

Generate interactive frontend elements when the use case needs a lightweight interface.

Functions

Specialized backend actions

Create focused capabilities for reporting, search, integrations, lead handling, and more.

The difference

Most AI stacks generate code. Hyperlambda compiles execution.

Typical AI tooling

  • Generate source code as text
  • Validate after generation
  • Depend on external controls for safety
  • Risk fragile outputs and unsafe execution

Hyperlambda

  • Compile into strict ASTs
  • Bind only to allowed runtime capabilities
  • Execute inside a constrained runtime
  • Generate backend functionality quickly and safely
Proof, in writing

Read the receipts

The thesis

The only LLM on earth that grows its own tools securely, on demand, in production

Every agent framework ships with a fixed toolbox somebody had to build by hand. Mine writes new tools at runtime — statically verified, whitelist-sandboxed, and RBAC-locked before they ever execute.
The mechanism

Zero-hallucination code generation — a vocabulary your AI cannot escape

How Hyperlambda eliminates AI hallucinations with two runtime-backed gates: static function verification that refuses to return invalid code, and whitelist, a vocabulary the code cannot escape.
The outcome

A complete CRM in one conversation — 60 seconds of backend, six cents of tokens

A role-secured CRM — database, 20 endpoints, JWT auth, email dispatch, KPI dashboard — built in a single conversation over Magic's MCP. Full time, cost and bug ledger.
Ready to build

Give your agents safer backend leverage

Try Hyperlambda and see how natural language can compile into deterministic backend capabilities for AI agents.

Try the AST Playground Size the token savings for your team Back to homepage
terminal 
# Or run it locally — log in at http://localhost:5555 with root/root.
$ curl -fsSL https://hyperlambda.dev/docker-compose.yaml | docker compose -f - up