Gemini MCP Server (salviz/gemini-mcp-server) is an MCP server listed on the M8ven Trust Index. It scores 74 out of 100, grade C. It declares 23 tools. No publisher has claimed this listing.

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C
Caution
74/100

Gemini MCP Server

Provides 23 tools for Google's Gemini API, enabling chat, multimodal analysis, deep research, file management, and YouTube analysis via natural language.

→ salviz/gemini-mcp-server· listed on glama

Caution. Specific findings reduced this grade. They are listed on the page. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

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Who stands behind it

salviz

Source: Glama

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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
⚠️
Tool descriptions don’t match what handlers do
2 tools describe read intent but their handlers mutate — gemini_analyze_audio (line 23: execFile('termux-notification', [); gemini_analyze_video (line 23: execFile('termux-notification', [)
✅
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.
// tools this server exposes23 tools

These names and descriptions are the publisher's own, read from the source code. We print them as written. Our assessment is the findings above, not this list.

gemini_chat

Send a prompt to Gemini and get a text response. Optionally enable search grounding or URL context.

gemini_analyze_image

Analyze an image file with Gemini Vision

gemini_analyze_audio

Analyze an audio file with Gemini (transcribe, summarize, describe)

gemini_analyze_video

Analyze a video file with Gemini (describe, summarize, extract info)

gemini_analyze_pdf

Analyze a PDF document with Gemini (summarize, extract, answer questions)

gemini_chat_multi

Multi-turn conversation with Gemini using message history

gemini_search_grounded

Send a prompt to Gemini with Google Search grounding and URL context for up-to-date information

gemini_structured_output

Get structured JSON output from Gemini using a provided JSON schema

gemini_url_context

Analyze one or more URLs using Gemini URL context tool. Gemini fetches and reads the URLs directly.

gemini_chat_with_tools

Flexible Gemini chat with mode switching: "search" (Google Search + URL context), "code" (code execution), or "all" (everything)

gemini_deep_research

Start a deep research task using Gemini Deep Research. Returns an interaction ID. Then call gemini_check_research with wait=true in the background to get notified when complete.

gemini_check_research

Check or wait for deep research results. Use wait=true to block until completion (ideal for background execution — the tool returns when research finishes, triggering a task notification in your AI client).

gemini_upload_file

Upload a file to Gemini Files API for use with analysis tools. Files are retained for 48 hours. Max 2GB per file, 20GB total.

gemini_list_files

List files uploaded to the Gemini Files API

gemini_delete_file

Delete a file from the Gemini Files API

gemini_analyze_youtube

Analyze a public YouTube video with Gemini (summarize, transcribe, answer questions). Supports up to 10 videos with Gemini 2.5+ models.

gemini_analyze_url

Analyze a file from a public URL (HTTP/HTTPS) or Google Cloud Storage URI (gs://). Supports images, audio, video, PDFs, and documents up to 100MB.

gemini_list_models

List available Gemini models with their capabilities and token limits

gemini_count_tokens

Count the number of tokens in the provided text using a Gemini model

gemini_embed

Generate text embeddings using a Gemini embedding model

gemini_code_execute

Generate and execute code using Gemini's built-in code execution capability

gemini_summarize

Summarize long text using Gemini with configurable summary style

gemini_translate

Translate text to a target language using Gemini

// 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

23/23 tools missing one or more hints — gemini_chat (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); gemini_analyze_image (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); gemini_analyze_audio (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +20 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.

Descriptions match behaviour

2 tools describe read intent but their handlers mutate — gemini_analyze_audio (line 23: execFile('termux-notification', [); gemini_analyze_video (line 23: execFile('termux-notification', [)

Rename the tool, rewrite the description, or move the side-effect into a separate clearly-named tool.

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: 0442ce1391f28cb7fd6e29988288eebdea3eae4f
code hash: 0ebdd69aacb425ee83dc1ba2dbc5b8a7e805f374c6fb9cf69cb12f5aacfb3fd5
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