io.github.rafapra3008/lu-mcp-server

Official

by rafapra3008 · Python

Lingua Universale MCP Server

Verify AI agent communication with session types and formal proofs

Verifies AI agent communication using session types and formal proofs.

Topics

ai-agentsformal-verificationmcpprogramming-languageprotocol-verificationsession-types

README.md9 KBView on GitHub

Lingua Universale

A language for verified AI agent protocols.

Try it in your browser -- no install needed. Watch AI agents live -- 3 agents on a verified protocol.

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The Problem

Your AI agents talk to each other, but nothing guarantees they follow the rules. Wrong sender, wrong message order, missing steps -- and you only find out in production.

Lingua Universale (LU) is a type checker for AI agent conversations. You define the protocol, LU proves it's correct, and the runtime enforces it.

python

from cervellaswarm_lingua_universale import Protocol, ProtocolStep, MessageKind, SessionChecker, TaskRequest

# Define: who sends what, to whom, in what order
review = Protocol(name="Review", roles=("dev", "reviewer"), elements=(
    ProtocolStep(sender="dev", receiver="reviewer", message_kind=MessageKind.TASK_REQUEST),
    ProtocolStep(sender="reviewer", receiver="dev", message_kind=MessageKind.TASK_RESULT),
))

checker = SessionChecker(review)
checker.send("dev", "reviewer", TaskRequest(task_id="1", description="Review auth"))  # OK
checker.send("dev", "reviewer", TaskRequest(task_id="2", description="Oops"))         # ProtocolViolation!
#                                                                                      ^^^ wrong turn: reviewer must send next

The protocol says reviewer goes next. The runtime blocks it. Not because you trust the code -- because the session type makes it impossible.

Install

bash

pip install cervellaswarm-lingua-universale

Or try it first: Playground (runs in your browser via Pyodide).

Write a Protocol

code

protocol DelegateTask:
    roles: supervisor, worker, validator

    supervisor asks worker to execute analysis
    worker returns result to supervisor
    supervisor asks validator to verify result

    when validator decides:
        pass:
            validator returns approval to supervisor
        fail:
            validator sends feedback to supervisor

    properties:
        always terminates
        no deadlock
        no deletion
        all roles participate

Then verify it:

bash

lu verify delegate_task.lu

code

  [1/4] always_terminates  ... PROVED
  [2/4] no_deadlock        ... PROVED
  [3/4] no_deletion        ... PROVED
  [4/4] all_roles_participate ... PROVED

  All 4 properties PASSED.

Mathematical proof. Not a test that passes today and fails tomorrow.

What You Get

Feature	Description
Full compiler	Tokenizer, parser (64 rules), AST, contract checker, Python codegen
9 verified properties	`always_terminates`, `no_deadlock`, `no_deletion`, `role_exclusive`, and more
20 stdlib protocols	AI/ML, Business, Communication, Data, Security -- ready to use
Linter + Formatter	`lu lint` (10 rules) + `lu fmt` (zero-config, like gofmt)
LSP server	Diagnostics, hover, completion, go-to-definition, formatting
VS Code extension	Install from Marketplace
Interactive chat	`lu chat` -- build protocols conversationally (English, Italian, Portuguese)
Browser playground	Try it now -- Check, Lint, Run, Chat
Lean 4 bridge	Generate and verify mathematical proofs
REPL	`lu repl` for interactive exploration
Project scaffolding	`lu init --template rag_pipeline` from 20 verified templates

37 modules. 3979 tests. Zero external dependencies. Pure Python stdlib.

CLI

bash

lu check file.lu          # Parse and compile
lu verify file.lu         # Formal property verification
lu run file.lu            # Execute
lu lint file.lu           # 10 style and correctness rules
lu fmt file.lu            # Zero-config auto-formatter
lu chat --lang en         # Build a protocol conversationally
lu demo --lang it         # See the La Nonna demo
lu init --template NAME   # Scaffold from stdlib templates
lu visualize file.lu      # Generate Mermaid sequence diagram
lu mcp-audit --manifest t.json  # Audit MCP server protocols
lu repl                   # Interactive REPL
lu lsp                    # Start LSP server

CI Integration

Add protocol verification to your GitHub Actions workflow:

yaml

# .github/workflows/lu-check.yml
on:
  push:
    paths: ["**/*.lu"]

jobs:
  lu-check:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v6
        with:
          python-version: "3.11"
      - run: pip install cervellaswarm-lingua-universale
      - run: lu lint protocols/
      - run: lu verify protocols/

Exit code is non-zero on violations -- works with any CI system.

How It Works

LU is built on multiparty session types (Honda, Yoshida, Carbone -- POPL 2008). Session types describe communication protocols as types: if two processes follow the same session type, they cannot deadlock, messages cannot arrive in the wrong order, and the conversation always terminates.

The pipeline:

code

.lu source → Tokenizer → Parser → AST → Spec Checker → Lean 4 Proofs → Python Codegen
                                           ↓
                                    PROVED or VIOLATED

LU doesn't replace your AI agent framework. It makes it safe. Like TypeScript for JavaScript -- you keep your tools, you add guarantees.

Examples

LU Debugger -- Live web app: 3 AI agents (Customer, Warehouse, Payment) communicate on a verified OrderProcessing protocol. Click "Break" to see a protocol violation blocked in real time. Source code.

See the examples/ directory:

Agent Orchestration -- 3 AI agents with nested choice, 8/8 properties proved
Live Runner -- Real Claude API agents on a verified protocol
Standard Library -- 20 verified protocols across 5 categories

Or try the interactive Colab notebook -- 2 minutes, zero setup.

More from CervellaSwarm

Lingua Universale is the core project by CervellaSwarm. We also publish these Python packages:

Package	What it does
code-intelligence	AST-powered code understanding (tree-sitter, PageRank)
agent-hooks	Lifecycle hooks for Claude Code agents
agent-templates	Agent definition templates & team configuration
task-orchestration	Deterministic task routing & validation
spawn-workers	Multi-agent process management
session-memory	Persistent session context across conversations
event-store	Immutable event logging & audit trail
quality-gates	Automated quality checks & scoring

All Apache 2.0, Python 3.10+, tested, documented.

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Bug reports: GitHub Issues
Security: See SECURITY.md for responsible disclosure

License

Apache License 2.0 -- see LICENSE.

Lingua Universale -- Verified protocols for AI agents.

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Install

claude_desktop_config.json

{
  "mcpServers": {
    "lu-mcp-server": {
      "command": "uvx",
      "args": [
        "lu-mcp-server"
      ]
    }
  }
}