Local LLM MCP Tool (Marcel-MSC/local-llm-mcp-tool) is an MCP server listed on the M8ven Trust Index. It scores 71 out of 100, grade C. It declares 11 tools. No publisher has claimed this listing.

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C
Limited view
71/100

Local LLM MCP Tool

A local MCP server that runs Llama models entirely on your machine. No API keys, no cloud costs, 100% private and offline-capable.

→ Marcel-MSC/local-llm-mcp-tool· listed on glama

Limited view. Automated analysis covers part of this stack. Findings reflect what we verified. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

Limited view: static analysis for Python is partially covered.

How we verified

Code Verified⚡ Live Monitored: not connected

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Who stands behind it

Marcel-MSC

Source: Glama

Is this your MCP?

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Install from

Glamanot scored here

The grade above is for the source repository. Registries can serve a different version, so we mark the ones we were not able to read.

// key findings
✅
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
✅
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
// environment variables
To run this server yourself, you supply these values. They go in your own MCP client configuration and stay on your machine. The secret label means the value is sensitive, not that the server mishandles it.
configMODEL_PATHC:\path\to\your\model.gguf
configN_THREADSNumber of CPU threads 4
configN_GPU_LAYERSGPU layers (use -1 for all, 0 for CPU only) 0
configCONTEXT_SIZEMaximum context window size 2048
configSESSION_HISTORY_DIRDirectory for storing conversation history history
configSESSION_MAX_MESSAGESMaximum messages per session (older messages trimmed) 40
configSESSION_MAX_FILE_BYTESMaximum size per session file (bytes) 2097152 (~2MB)
configSESSION_AUTO_TRIMAutomatically trim history when limits exceeded true
configSTREAMING_ENABLEDEnable streaming responses (tokens sent incrementally) false
configSTREAMING_CHUNK_SIZEApproximate chunk size for streaming (characters) 50
configMODELS_DIR
Deployment configuration, supplied by whoever hosts the server. Users are not asked for these.
deployPORT
// quality suggestions

Tool annotations

No tools have read-only/destructive annotations

Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.

All four hints declared on every tool

11/11 tools missing one or more hints — generate_text (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); chat (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); complete (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +8 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.

For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.

Tool handlers catch errors

Only 0/3 tool handlers wrap calls in try/catch (0%)

Wrap each tool handler body in try/catch and return a structured error response.

Tests exist

No test files found

Add tests that exercise each declared tool.

Claim the listing to review these findings one by one and send us a correction where you disagree, straight to the team. Claiming also means we tell you when the grade moves, and reach you first if we find anything urgent.

// full audit trail
The findings above are the summary. The full trail, every check we ran, each deduction, the network hosts observed and the dependency advisories, goes to verified publishers, along with an alert whenever a new one lands. Verified publishers can also review each finding and dispute it in one click. Publisher corrections have sharpened several of our checks this month, because the maintainer knows the codebase better than any scanner.
// improvement guidance — verified publishers only
We have 4 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
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commit: a2b5d0f29ab8f419f29d8a9d9ac773a39aa436dd
code hash: becde44ba9c05464cf989554b4a7fbe3db511976b09f7debec501f8c6639eaa7
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