Install
$ agentstack add mcp-bneb-trytet ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Trytet
[](https://github.com/bneb/trytet/releases) [](https://www.npmjs.com/package/trytet-client) [](https://pypi.org/project/trytet-client/)
A WebAssembly sandbox engine that runs AI-generated code without crashing. Agents invoke deterministic Wasm components ("cartridges") inside fuel-bounded sandboxes — infinite loops trap in microseconds instead of hanging until a timeout, memory bombs get capped instead of OOMing.
Installation
# macOS (Apple Silicon)
curl -sL https://github.com/bneb/trytet/releases/latest/download/tet-darwin-arm64.tar.gz | tar xz
./tet doctor
./tet mcp --list-tools
# Docker
docker pull ghcr.io/bneb/trytet:latest
docker run -p 3000:3000 ghcr.io/bneb/trytet:latest
Also available via SDK: npm install trytet-client | pip install trytet-client
Quickstart
Claude Desktop / Cursor — add to claude_desktop_config.json:
{
"mcpServers": {
"trytet": {
"command": "tet",
"args": ["mcp"]
}
}
}
Then tools appear automatically. Run tet mcp --list-tools to verify.
SDK — call Trytet from your own agent code:
npm install trytet-client # TypeScript
pip install trytet-client # Python
API server:
tet up # Starts on port 3000
curl http://localhost:3000/health # Health check
Performance
| Operation | Latency | |---|---| | Cached cartridge call | <500µs | | First cartridge call (Cranelift compilation) | ~400ms (one-time, cached) | | MCP server boot | ~50ms | | Infinite loop trap | <100µs (instruction-level fuel exhaustion) |
MCP Tools
Trytet exposes 5 tools via the Model Context Protocol (3 ship with compiled .wasm, 2 experimental):
| Tool | Status | |---|---| | trytet_js_evaluator | shipped — Execute JavaScript with fuel and memory limits | | trytet_regex_evaluator | shipped — Run regex patterns safely (ReDoS-protected) | | trytet_jmespath_evaluator | shipped — Query JSON with JMESPath expressions | | trytet_scraper | experimental — Parse HTML with CSS selectors | | trytet_structured_data | experimental — SQLite-powered queries over JSON arrays |
Architecture
Three layers:
- Sandbox — Wasmtime engine with instruction-level fuel metering. Each Wasm instruction deducts from a fuel budget. Exhaustion produces a deterministic trap — no wall-clock timeouts, no OS process overhead.
- Cartridge Substrate — Wasm Components are loaded, compiled, and executed in sub-sandboxes with independent fuel and memory limits. The host controls all resources; cartridges own nothing.
- Hive Mesh (experimental) — Agent snapshot, fork, and teleport between nodes for state migration.
Measured Performance
- MCP Server boot: ~50ms
- Cached cartridge call: <500µs
- First cartridge call: ~400ms (Cranelift compilation, one-time)
- Test suite: 0 failures across 64 test files
Detailed benchmarks: [BENCHMARKS.md](BENCHMARKS.md)
CLI
tet up # Start the API server
tet mcp # Start the MCP server (for Claude Desktop, Cursor)
tet ps # List running agents
tet metrics # Run benchmark suite
tet init [name] # Scaffold a new agent project
Full reference: [CLI.md](CLI.md)
SDKs
npm install trytet-client # TypeScript
pip install trytet-client # Python
Project Status
The core sandbox engine, cartridge substrate, and MCP server are functional. The project is under active development. Production deployments should pin to a specific release.
License
MIT
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: bneb
- Source: bneb/trytet
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.