io.github.yasmanycastillo/model-shunt
PYPI · MODEL-SHUNT · 2 COMPONENTS · SCANNED SEP 25
Model routing for AI agents: delegate bulk reads & boilerplate to cheap worker models.
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 Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- No production dependencies, so there is no dependency health to assess. View diagnostics → Pass
Provenance & Transparency32
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- License check failed: the license (MIT License) isn't a recognized OSI-approved license. See how to fix → Fail
- Actively maintained (last published 1 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability80
- AI-judged instruction clarity (excellent).Pass
- Tool/resource definitions use about 365 tokens (~121/item across 3 items; 3 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
- Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
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 Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 3 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 3 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities60
- Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28. See how to fix → Fail
Unverified: 1 category
A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.
How do I install the io.github.yasmanycastillo/model-shunt MCP server?
io.github.yasmanycastillo/model-shunt runs locally as a PyPI package, launched with uvx model-shunt. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · model-shunt
claude mcp add yasmanycastillo-model-shunt -- uvx model-shunt
{
"mcpServers": {
"yasmanycastillo-model-shunt": {
"command": "uvx",
"args": [
"model-shunt"
]
}
}
} {
"servers": {
"yasmanycastillo-model-shunt": {
"command": "uvx",
"args": [
"model-shunt"
]
}
}
} codex mcp add yasmanycastillo-model-shunt -- uvx model-shunt
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"yasmanycastillo-model-shunt": {
"type": "local",
"command": [
"uvx",
"model-shunt"
],
"enabled": true
}
}
} openclaw mcp add yasmanycastillo-model-shunt --command uvx --arg model-shunt
mcp_servers:
yasmanycastillo-model-shunt:
command: "uvx"
args: ["model-shunt"] {
"McpServers": {
"yasmanycastillo-model-shunt": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"model-shunt"
]
}
}
} assistant mcp add yasmanycastillo-model-shunt -t stdio -c uvx -a model-shunt
{
"mcpServers": {
"yasmanycastillo-model-shunt": {
"command": "uvx",
"args": [
"model-shunt"
]
}
}
} 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.
- 25 Sept 26 +15
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 24 Sept 26 52
First indexed and scored.
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 25 Sept 2026 · Analysed pypi/model-shunt@1.2.1
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 0 packages
| Packages resolved | 0 |
|---|---|
| Tree resolution | Complete |
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 →
bulk_read ~132
Reads multiple or large files and answers a targeted question using a cheap, fast worker model (e.g. Gemini Flash, Groq, Ollama). Saves ~90% tokens by returning only structured bullet points.
| Name | Type | Req | Description |
|---|---|---|---|
| file_paths | array | yes | List of file paths to analyze |
| model | string | – | Optional model override (or 'auto' to select the best available reader model) |
| provider | string | – | Optional provider override (gemini, groq, openai, deepseek, anthropic, ollama, openrouter) |
| question | string | yes | The specific question to answer about the files |
No output schema declared.
No examples provided.
code_write ~148
Generates boilerplate code (tests, mocks, stubs, configs) matching the patterns of a reference file. Can write directly to disk without consuming frontier output tokens.
| Name | Type | Req | Description |
|---|---|---|---|
| model | string | – | Optional model override (or 'auto' to select the best available writer model) |
| provider | string | – | Optional provider override (gemini, groq, openai, deepseek, anthropic, ollama, openrouter) |
| reference_path | string | yes | Path to reference file whose conventions, style, and structure should be replicated |
| spec | string | yes | Description of what code to generate |
| target_path | string | – | Optional path where generated code should be written directly on disk |
No output schema declared.
No examples provided.
get_available_models ~85
Discovers active models from the worker provider and recommends the best model for reading (high context / low cost) and writing (code intelligence). Enables calling agents to delegate dynamically to the best model.
| Name | Type | Req | Description |
|---|---|---|---|
| provider | string | – | Optional provider to query (gemini, groq, openai, deepseek, anthropic, ollama, openrouter). Defaults to active provider. |
No output schema declared.
No examples provided.
What is the io.github.yasmanycastillo/model-shunt MCP server?
io.github.yasmanycastillo/model-shunt is an MCP server listed in the public MCP registry as io.github.yasmanycastillo/model-shunt. Model routing for AI agents: delegate bulk reads & boilerplate to cheap worker models. This page covers its PyPI package (model-shunt).
Is the io.github.yasmanycastillo/model-shunt MCP server safe to use?
io.github.yasmanycastillo/model-shunt scores 67 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 25 September 2026. 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 io.github.yasmanycastillo/model-shunt MCP server expose?
io.github.yasmanycastillo/model-shunt exposes 3 tools: bulk_read, code_write, get_available_models. Their descriptions and schemas cost roughly 365 tokens of context every time the server is loaded.
Is the io.github.yasmanycastillo/model-shunt MCP server still maintained?
io.github.yasmanycastillo/model-shunt is still listed as active in the MCP registry. We last reached this channel on 25 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.