MCP Sandbox Computer VM for AI
PYPI · MCP-SANDBOX-COMPUTER-VM-FOR-AI · SCANNED OCT 4
Named Docker and Fly Machine sandbox computers with an interactive MCP App dashboard.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security39
- Malware scan not yet available for this package.Unverified
- Known CVEs were checked across the 48 of 67 dependencies we could resolve, so this covers what we could see, not the whole tree.Partial
- No install/post-install scripts declared.Pass
- Dependency health was assessed across the 48 of 67 dependencies we could resolve, so this covers what we could see, not the whole tree. View diagnostics → Partial
Provenance & Transparency97
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to flujo-app/mcp-sandbox-computer-vm-for-ai). View diagnostics → Pass
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 27 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability75
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 247 tokens (~247/item across 1 items; 1 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management90
- Stability observed for 27 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Tool Safety75
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- 0 of 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation; "terminal_execute" implies "execute" and declares no destructiveHint at all, which the MCP spec reads as destructive by default. See how to fix → Fail
- An AI judge read all 1 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
How do I install the MCP Sandbox Computer VM for AI server?
MCP Sandbox Computer VM for AI runs locally as a PyPI package, launched with uvx mcp-sandbox-computer-vm-for-ai. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · mcp-sandbox-computer-vm-for-ai
claude mcp add flujo-app-mcp-sandbox-computer-vm-for-ai -- uvx mcp-sandbox-computer-vm-for-ai
{
"mcpServers": {
"flujo-app-mcp-sandbox-computer-vm-for-ai": {
"command": "uvx",
"args": [
"mcp-sandbox-computer-vm-for-ai"
]
}
}
} {
"servers": {
"flujo-app-mcp-sandbox-computer-vm-for-ai": {
"command": "uvx",
"args": [
"mcp-sandbox-computer-vm-for-ai"
]
}
}
} codex mcp add flujo-app-mcp-sandbox-computer-vm-for-ai -- uvx mcp-sandbox-computer-vm-for-ai
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"flujo-app-mcp-sandbox-computer-vm-for-ai": {
"type": "local",
"command": [
"uvx",
"mcp-sandbox-computer-vm-for-ai"
],
"enabled": true
}
}
} openclaw mcp add flujo-app-mcp-sandbox-computer-vm-for-ai --command uvx --arg mcp-sandbox-computer-vm-for-ai
mcp_servers:
flujo-app-mcp-sandbox-computer-vm-for-ai:
command: "uvx"
args: ["mcp-sandbox-computer-vm-for-ai"] {
"McpServers": {
"flujo-app-mcp-sandbox-computer-vm-for-ai": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"mcp-sandbox-computer-vm-for-ai"
]
}
}
} assistant mcp add flujo-app-mcp-sandbox-computer-vm-for-ai -t stdio -c uvx -a mcp-sandbox-computer-vm-for-ai
{
"mcpServers": {
"flujo-app-mcp-sandbox-computer-vm-for-ai": {
"command": "uvx",
"args": [
"mcp-sandbox-computer-vm-for-ai"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 4 Oct 26 −2
- Known CVEs: pass → partial ▼ security
- Dependency health: 0.96 → partial functional
- 3 Oct 26 +12
- Stability: fail → 0.87 functional
- 29 Sept 26 −15
- Malware scan: pass → unverified ▼ security
- 28 Sept 26 +25
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 27 Sept 26 −15
- Malware scan: pass → unverified ▼ security
- Package version: 0.2.2 → 0.2.3 functional
- 26 Sept 26 +15
- Malware scan: unverified → pass ▲ security
- 25 Sept 26 −12
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 18 Sept 26 +15
- Malware scan: unverified → pass ▲ security
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 8 Oct 2026 · Analysed pypi/mcp-sandbox-computer-vm-for-ai@0.2.3
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | pypi |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | flujo-app/mcp-sandbox-computer-vm-for-ai |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/flujo-app/mcp-sandbox-computer-vm-for-ai/.github/workflows/release.yml@refs/tags/v0.2.3 |
| Rekor log index | 2743948470 |
| Predicate type | PyPI publish attestation https://docs.pypi.org/attestations/publish/v1 |
| Subject digest | sha256:97a7c16e32086f77b33c9e1871099b42e6cef37c0cbaf8c08f1d0f9dc7d5c34a |
Background: How many MCP packages publish verified provenance →
Dependencies 61 packages
| Packages resolved | 61 |
|---|---|
| Stale | 4 |
| No linked repository | 1 |
| Tree resolution | Partial |
The dependency tree was only partially resolved, so these counts may be incomplete.
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
terminal_execute ~247
Execute a shell command in an isolated Debian Linux sandbox. Commands run in bash. Each call is independent — no state (shell variables, working directory) persists between calls (however filesystem does persist). Use the working_directory parameter or chain commands with && to control execution context. To write files or pass data without shell escaping, use the stdin parameter (e.g., command="cat > file.txt" with content in stdin). Commands time out after 120 seconds by default (override with the timeout parameter for long-running operations).
| Name | Type | Req | Description |
|---|---|---|---|
| args | array | – | List of arguments for direct execution (mutually exclusive with command). |
| command | string | – | Shell command string (mutually exclusive with args). |
| computer_id | string | – | Stable computer slug. Omit to create and select a readable random ID for this MCP session. |
| stdin | string | – | Content to pipe to stdin. |
| temporary | boolean | – | Remove the computer when its MCP session shuts down. Set false to keep it provider-side and reconnect by computer_id. |
| timeout | integer | – | Timeout in seconds (defaults to server config). |
| working_directory | string | – | Working directory for the command (must be absolute). |
No output schema declared.
No examples provided.
What is the MCP Sandbox Computer VM for AI server?
MCP Sandbox Computer VM for AI is listed in the public MCP registry as io.github.flujo-app/mcp-sandbox-computer-vm-for-ai. Named Docker and Fly Machine sandbox computers with an interactive MCP App dashboard. This page covers its PyPI package (mcp-sandbox-computer-vm-for-ai).
Is the MCP Sandbox Computer VM for AI server safe to use?
MCP Sandbox Computer VM for AI scores 74 out of 100 on VerifyMCP. It declares no install or post-install scripts. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the MCP Sandbox Computer VM for AI server expose?
MCP Sandbox Computer VM for AI exposes 1 tool: terminal_execute. Their descriptions and schemas cost roughly 247 tokens of context every time the server is loaded.
Is the MCP Sandbox Computer VM for AI server still maintained?
MCP Sandbox Computer VM for AI is still listed as active in the MCP registry. We last reached this channel on 4 October 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the MCP Sandbox Computer VM for AI server under?
MCP Sandbox Computer VM for AI declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.