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Registry/Omni AI MCP Server

Omni AI MCP Server

Verified

Full-featured MCP server for Google Gemini. multiple tools: text generation with thinking mode, code review, web search with citations, RAG document search, native image generation (4K), Veo 3.1 video with audio, text-to-speech with 30 voices and others. Works with Claude Code

MIT
other
ai ml
11stars
Scanned Oct 2, 2026
RepositoryGITHUB
Automated scan (limited checks) · 2026-10-02

This grade comes from an automated MCPSafe scan of the server's JavaScript, TypeScript and Python source on 2026-10-02. It read the whole repository (70 files). It checks for leaked credentials, shell or code injection from function inputs, unsafe deserialization, malware signatures, install-time scripts, and weak password handling. It does not check for path traversal, server-side request forgery, prompt injection in tool descriptions, network exposure, SQL injection, cross-site scripting, or vulnerable dependencies. It has not been manually reviewed, and the code may have changed since the scan.

A+100%
Scanned 1w ago

Excellent Security

Vulnerabilities Found
0Crit
0High
0Med
0Low
2Info

Trust Score 74

Review required
Trust grade B

Trust is stricter than security: it combines reviewed security, MCP capability risk, supply-chain metadata, quality, popularity, freshness, and penalties for unknowns.

Security
100
MCP risk
44
Supply chain
92
Maintenance
55
Docs
100
Freshness
80
Risk traits
Runs shell commands
Filesystem access
Network/API access
Requires secrets
Database access
Why it scores well
  • • No reviewed severe vulnerabilities published
  • • Good documentation surface
  • • Solid supply-chain metadata
  • • Recently scanned
What reduces confidence
  • • MCP risk traits: Runs shell commands, Filesystem access, Network/API access

Security ScoreA+

100
out of 100

Vulnerabilities Found

0
Crit
0
High
0
Medi
0
Low
2
Info
Last scanned: 10/2/2026

Quality ScoreC

62
out of 100
55
Maint.
11
Popular
100
Docs
72
Compat
Maintenance55%
Popularity11%
Documentation100%
Compatibility72%

Maintenance55

Unknown
Commit Frequency65%
Release Frequency35%
Issue Response65%

Popularity11

11
Stars
0
Downloads
0
Forks
Stars Score30%
Downloads Score0%
Forks Score0%

Documentation100

README Quality100%

Available Documentation

API DocsExamplesChangelog

Compatibility72

MCP Spec Compliance80%
Transport Support75%

Features

TypeScript

Supported Transports

STDIO

Vulnerabilities(0)

This grade comes from an automated scan. Individual findings from automated scans are not published.

READMEOmni AI MCP Server

View source

omni-ai-mcp

The complete AI bridge for Claude Code — Gemini's exclusive capabilities (video, TTS, 1M context, RAG, Deep Research) plus 400+ models via OpenRouter. One MCP server, every AI model, zero friction.

![License: MIT](https://opensource.org/licenses/MIT)

![Python 3.9+](https://www.python.org/downloads/)

![Version 4.4.0](https://github.com/marmyx77/omni-ai-mcp/releases)

![PyPI](https://pypi.org/project/omni-ai-mcp/)

![MCP Compatible](https://modelcontextprotocol.io/)


Why This Exists

Claude is exceptional at reasoning and code generation. But sometimes you need more:

  • A second opinion from a different AI model (GPT-4o, Llama, Mistral, Claude via OpenRouter)
  • Real-time web search with Google grounding and source citations
  • Autonomous deep research that runs for minutes and produces structured reports from 40+ sources
  • Video generation with Veo 3.1 — the only MCP server with native audio video generation
  • Image generation with Gemini 3 Pro Image (Nano Banana Pro) up to 4K resolution
  • Text-to-speech with 30 natural voices and multi-speaker support
  • RAG for querying your own documents with citations
  • Large codebase analysis with Gemini's 1M token context window
  • Multi-turn conversations with cloud persistence (55-day retention, resume from any device)
  • Access to 400+ models through one unified interface

omni-ai-mcp bridges Claude Code with Google Gemini and OpenRouter, enabling Claude to orchestrate any AI model as a tool.


What's New in v4.4.0

All model defaults are now aligned with the latest Gemini IDs, verified live against the Gemini API:

  • Text Flash → gemini-3.5-flash · Flash-Lite → gemini-3.1-flash-lite
  • Image → gemini-3-pro-image (Nano Banana Pro) / gemini-3.1-flash-image (Nano Banana 2)
  • TTS → gemini-3.1-flash-tts-preview
  • Deep Research → deep-research-preview-04-2026 (fixes the previous 404 NOT_FOUND agent)

Every default stays overridable via the GEMINI_MODEL_* environment variables.

Multi-Provider: Gemini + OpenRouter

Quick start

python
# Ask any of 400+ models — auto-routes from model name
ask_model("Explain quantum computing", model="openai/gpt-4o")
ask_model("Write a poem", model="meta-llama/llama-3.3-70b-instruct")
ask_model("Review this code", model="gemini-3.1-pro-preview")  # auto-routes to Gemini native API

# If no Gemini key but OpenRouter key exists, Gemini models route via OpenRouter automatically
ask_model("Summarize this", model="gemini-3.5-flash")  # -> google/ prefix on OpenRouter

# Discover all available models
gemini_list_models()

Dynamic Model Registry

No more hardcoded model IDs. The server discovers available models at runtime and always uses the latest. If a model is deprecated, it automatically falls back to the next available option.

bash
# Override via env vars if needed:
export GEMINI_MODEL_PRO=gemini-3.1-pro-preview
export OPENROUTER_DEFAULT_MODEL=openai/gpt-4o

Smart Routing Rules

  1. Explicit Gemini model + GEMINI_API_KEY -> always Gemini native API (fastest, cheapest)
  2. Gemini model + no Gemini key + OPENROUTER_API_KEY -> OpenRouter google/ prefix (automatic fallback)
  3. veo-*, imagen-*, deep-research-* models -> Gemini native only (no OpenRouter equivalent)
  4. OpenRouter model (openai/, meta-llama/, etc.) -> OpenRouter (requires OPENROUTER_API_KEY)

PyPI Distribution

bash
pip install omni-ai-mcp
omni-ai-mcp-setup  # interactive setup wizard

Claude Desktop Extension (.dxt)

Install with one click — no Python setup required:

  1. Download omni-ai-mcp-vX.Y.Z.dxt from GitHub Releases
  2. Double-click the file (macOS/Windows) or drag it into Claude Desktop
  3. Enter your Gemini API key when prompted (OpenRouter key is optional)
  4. Done — all 20 tools are immediately available in Claude Desktop

The .dxt bundle includes all Python dependencies — users don't need to install anything else.


20 Tools

Multi-Provider

| Tool | Description |

|------|-------------|

| ask_model | Ask any AI: Gemini or 400+ models via OpenRouter — auto-routes from model name |

| gemini_list_models | Live model discovery: Gemini registry + OpenRouter catalog, deprecation warnings |

Text & Reasoning

| Tool | Description | Model |

|------|-------------|-------|

| ask_gemini | Text generation with thinking mode, multi-turn, dual storage (local/cloud) | Gemini 3.1 Pro |

| gemini_code_review | Security, performance, and quality analysis | Gemini 3.1 Pro |

| gemini_brainstorm | Creative ideation with 6 methodologies (SCAMPER, TRIZ, etc.) | Gemini 3.1 Pro |

| gemini_challenge | Devil's advocate — find flaws in ideas, plans, and code | Gemini 3.1 Pro |

Code

| Tool | Description | Model |

|------|-------------|-------|

| gemini_analyze_codebase | Whole-codebase analysis up to 1M tokens / 5MB | Gemini 3.1 Pro |

| gemini_generate_code | Structured code generation with dry-run preview and XML output | Gemini 3.1 Pro |

Research & Web

| Tool | Description | Model |

|------|-------------|-------|

| gemini_web_search | Real-time search with Google grounding & citations | Gemini 3 Flash |

| gemini_deep_research | Autonomous 5-60 min research, 40+ sources, structured report | Deep Research Agent |

RAG

| Tool | Description |

|------|-------------|

| gemini_file_search | Query documents with citations |

| gemini_create_file_store | Create document stores |

| gemini_upload_file | Upload PDF, DOCX, code, etc. |

| gemini_list_file_stores | List available stores |

Media (Gemini exclusive)

| Tool | Description | Model |

|------|-------------|-------|

| gemini_analyze_image | Vision: describe, OCR, Q&A on images | Gemini 3 Flash |

| gemini_generate_image | Imagen — up to 4K resolution | Gemini 3 Pro Image |

| gemini_generate_video | Veo 3.1 — 4-8s with native audio (dialogue, effects, ambient) | Veo 3.1 |

| gemini_text_to_speech | 30 natural voices, multi-speaker dialogue | Gemini 2.5 Flash TTS |

Conversation

| Tool | Description |

|------|-------------|

| gemini_list_conversations | List history: title, mode, turns, last activity |

| gemini_delete_conversation | Delete by ID or title (partial match) |


Quick Start

Prerequisites

Install from PyPI (Recommended)

bash
pip install omni-ai-mcp
omni-ai-mcp-setup

The setup wizard configures Claude Code automatically.

Install from Source

bash
git clone https://github.com/marmyx77/omni-ai-mcp.git
cd omni-ai-mcp

# Gemini only
./setup.sh YOUR_GEMINI_API_KEY

# Gemini + OpenRouter (400+ models)
./setup.sh YOUR_GEMINI_API_KEY YOUR_OPENROUTER_KEY

Restart Claude Code. Verify:

bash
claude mcp list
# omni-ai-mcp: Connected

Manual Install

bash
pip install 'mcp[cli]>=1.0.0' 'google-genai>=2.0.0' pydantic defusedxml filelock

mkdir -p ~/.claude-mcp-servers/omni-ai-mcp
cp -r app/ run.py pyproject.toml ~/.claude-mcp-servers/omni-ai-mcp/

claude mcp add omni-ai-mcp --scope user \
  -e GEMINI_API_KEY=YOUR_KEY \
  -e OPENROUTER_API_KEY=YOUR_OR_KEY \
  -- python3 ~/.claude-mcp-servers/omni-ai-mcp/run.py

Usage Examples

Multi-Model AI Orchestration

plaintext
"Ask GPT-4o to review this authentication function"
-> ask_model(model="openai/gpt-4o", prompt="review this auth function...")

"Compare how Gemini and Llama respond to this design question"
-> ask_model(model="gemini-3.1-pro-preview", ...)
-> ask_model(model="meta-llama/llama-3.3-70b-instruct", ...)

"Get a Mistral opinion on this French legal document"
-> ask_model(model="mistralai/mistral-large-2512", ...)

Conversations with Memory

Gemini remembers previous context across calls via continuation_id:

plaintext
# First turn
"Ask Gemini to analyze @src/auth.py for security issues"
# Returns: continuation_id: abc-123

# Follow-up — Gemini remembers the previous analysis
"Ask Gemini (continuation_id: abc-123) how to fix the SQL injection"

Dual Storage Mode

| Mode | Storage | Retention | Use |

|------|---------|-----------|-----|

| local (default) | SQLite | 3h (configurable) | Development, quick chats |

| cloud | Google Interactions API | 55 days | Long projects, cross-device |

plaintext
# Start a named cloud conversation
"Ask Gemini (mode=cloud, title='Architecture Review'): Analyze my microservices design"
# Returns: continuation_id: int_v1_abc123...

# Resume from any device within 55 days
"Ask Gemini (continuation_id: int_v1_abc123...): What about the database layer?"

Deep Research

Autonomous research agent that runs 5-60 minutes:

plaintext
"Deep research: Compare AI agent frameworks in 2025 — LangGraph, AutoGen, CrewAI"

The agent will:

  1. Plan a comprehensive research strategy
  2. Execute multiple targeted web searches
  3. Synthesize findings from 40+ sources
  4. Produce a structured report with citations

Use cases: market research, competitive analysis, technical deep dives, trend analysis, literature reviews.

Codebase Analysis

Leverage Gemini's 1M token context to analyze entire codebases at once:

plaintext
"Analyze codebase src/**/*.py with focus on security"
"Analyze codebase ['app/', 'tests/'] — find architecture issues"

Analysis types: architecture, security, refactoring, documentation, dependencies, general

@File References

Include file contents directly in prompts:

plaintext
"Ask Gemini to review @src/auth.py for security issues"
"Brainstorm improvements for @README.md"
"Code review @*.py with focus on performance"
"Analyze codebase @src/**/*.ts"

Supported patterns: @file.py, @src/main.py, @*.py, @src/**/*.ts, @. (directory listing)

Video Generation

plaintext
"Generate a video of ocean waves at sunset, seagulls flying, sound of waves and wind"
  • Duration: 4-8 seconds
  • Resolution: 720p or 1080p (1080p requires 8s)
  • Native audio: dialogue, sound effects, ambient sounds
  • For dialogue: use quotes ("Hello," she said)
  • For sounds: describe explicitly (engine roaring, birds chirping)

Image Generation

plaintext
"Generate an image of a futuristic Tokyo street at night, neon lights reflecting on wet pavement,
cinematic, shot on 35mm lens"
  • Resolution: up to 4K with Pro model
  • Aspect ratios: 1:1, 16:9, 9:16, 3:2, 4:5, and more
  • Use descriptive sentences, not keyword lists

Text-to-Speech

plaintext
"Convert this article to speech using the Charon voice (informative, neutral)"

30 available voices — Bright: Zephyr, Autonoe / Upbeat: Puck, Laomedeia / Informative: Charon, Rasalgethi / Warm: Sulafat, Vindemiatrix / and 22 more.

Multi-speaker dialogue:

python
gemini_text_to_speech(
    text="Host: Welcome!\nGuest: Thanks for having me!",
    speakers=[
        {"name": "Host", "voice": "Charon"},
        {"name": "Guest", "voice": "Aoede"}
    ]
)

Image Analysis

plaintext
"Analyze this screenshot and extract all visible text: @screenshot.png"
"Describe what's in this diagram and explain the architecture: @diagram.png"

Supported formats: PNG, JPG, JPEG, GIF, WEBP

RAG (Document Search)

plaintext
# 1. Create a store
"Create a Gemini file store called 'project-docs'"

# 2. Upload files
"Upload the API specification PDF to the project-docs store"

# 3. Query
"Search the project-docs store: What are the rate limits?"

Challenge Tool

Get critical analysis before implementing — find flaws early:

plaintext
"Challenge this plan with focus on security:
We'll store user sessions in localStorage and use MD5 for passwords"

The tool acts as a Devil's Advocate — it will NOT agree with you.

Focus areas: general, security, performance, maintainability, scalability, cost

Code Generation

plaintext
"Generate a Python FastAPI endpoint for JWT authentication with refresh tokens"

Output is structured XML that Claude can apply directly:

xml
<GENERATED_CODE>
<FILE action="create" path="src/auth.py">
# Complete implementation here...
</FILE>
</GENERATED_CODE>

Options: dry_run=true to preview without writing, language, style (production/prototype/minimal), output_dir

Thinking Mode

plaintext
"Ask Gemini with high thinking level:
Design an optimal database schema for a social media platform at scale"

Levels: off (default), low (fast reasoning), high (deep analysis)


Model Selection

Text Models

| Alias | Resolved Model | Best For |

|-------|----------------|----------|

| pro | gemini-3.1-pro-preview | Complex reasoning, coding, analysis |

| flash | gemini-3.5-flash | Balanced speed/quality |

| fast / flash-lite | gemini-3.1-flash-lite | High-volume, simple tasks |

Models are resolved dynamically at runtime — if a model is deprecated, the registry automatically falls back to the next available option.

OpenRouter Models (via ask_model)

| Provider | Example Model ID | Notes |

|----------|-----------------|-------|

| OpenAI | openai/gpt-4o | GPT-4o, o3, o4-mini |

| Meta | meta-llama/llama-3.3-70b-instruct | Open source, fast |

| Anthropic | anthropic/claude-3.5-sonnet | Claude via OpenRouter |

| Mistral | mistralai/mistral-large-2512 | Strong on EU languages |

| Google | google/gemini-3.1-pro-preview | Gemini via OpenRouter (fallback) |

| 340+ more | — | gemini_list_models() to browse |


Configuration

All settings via environment variables:

| Variable | Default | Description |

|----------|---------|-------------|

| GEMINI_API_KEY | required | Google Gemini API key |

| OPENROUTER_API_KEY | — | OpenRouter key (enables ask_model for 400+ models) |

| GEMINI_MODEL_PRO | gemini-3.1-pro-preview | Override Pro text model |

| GEMINI_MODEL_FLASH | gemini-3.5-flash | Static fallback model |

| GEMINI_MODEL_DEEP_RESEARCH | deep-research-preview-04-2026 | Override research agent |

| OPENROUTER_DEFAULT_MODEL | openai/gpt-4o | Default OpenRouter model |

| OPENROUTER_TIMEOUT | 120 | OpenRouter generation timeout in seconds (raise for search models like perplexity/sonar-deep-research) |

| GEMINI_SANDBOX_ROOT | cwd | Root directory for file access |

| GEMINI_SANDBOX_ENABLED | true | Enable path sandboxing |

| GEMINI_MAX_FILE_SIZE | 102400 | Max file size in bytes (100KB) |

| GEMINI_CONVERSATION_TTL_HOURS | 3 | Local conversation expiry |

| GEMINI_CONVERSATION_MAX_TURNS | 50 | Max turns per thread |

| GEMINI_LOG_DIR | ~/.omni-ai-mcp | Log & DB directory |

| GEMINI_LOG_FORMAT | text | json or text |

| GEMINI_DISABLED_TOOLS | — | Comma-separated tool names to disable |


Claude Code Plugin

Slash Commands

Included in .claude/commands/ (auto-available in Claude Code when working inside this repo, or copy to ~/.claude/commands/ for global access):

| Command | Action |

|---------|--------|

| /gemini <prompt> | Ask Gemini Pro anything |

| /gemini-research <topic> | Autonomous deep research (40+ sources, 5-30 min) |

| /gemini-review <file> | Code review focused on bugs, security, performance |

| /gemini-challenge <idea> | Devil's Advocate — find flaws in a plan or architecture |

| /gemini-analyze <path> | Codebase analysis with 1M token context window |

| /gemini-brainstorm <topic> | Structured brainstorming (6 methodologies) |

| /gemini-models | List available models (Gemini + OpenRouter) |

| /ask-model [model] <prompt> | Ask any model: GPT-4o, Llama, Mistral, Gemini, etc. |

| /cowork <task> | Claude + Gemini working in parallel on the same task |

Subagents

Included in .claude/agents/ — Claude Code activates these automatically based on context:

| Agent | Trigger | Capability |

|-------|---------|------------|

| gemini-researcher | "research X", "investigate Y", "find sources on Z" | Deep Research Agent, 40+ sources |

| gemini-analyzer | "analyze codebase", "security audit", "review architecture" | 1M token context window |

| model-orchestrator | "ask GPT-4o", "compare models", "use Llama for this" | Routes to 400+ models via OpenRouter |

| cowork | "second opinion", "verify with Gemini", "stress test this" | Claude + Gemini parallel analysis with synthesis |

Install globally (all projects)

bash
cp -r .claude/commands/* ~/.claude/commands/
cp -r .claude/agents/* ~/.claude/agents/

Multi-Model Architecture

omni-ai-mcp uses Claude as the orchestrator with other models as tools:

plaintext
User -> Claude Code
            (orchestrates)
       omni-ai-mcp tools
       +-- ask_model("openai/gpt-4o")       -> OpenRouter -> GPT-4o
       +-- ask_model("meta-llama/...")       -> OpenRouter -> Llama 3
       +-- ask_model("gemini-3.1-pro...")    -> Gemini API (native)
       +-- ask_gemini(...)                   -> Gemini API -> Gemini Pro
       +-- gemini_deep_research(...)         -> Gemini API -> Deep Research Agent
       +-- gemini_generate_video(...)        -> Gemini API -> Veo 3.1

This is different from provider replacement tools like claude-code-router which replace Claude's backend entirely. omni-ai-mcp keeps Claude in control while giving it access to every AI model as a tool.


Architecture

plaintext
omni-ai-mcp/
+-- app/
|   +-- server.py              # FastMCP -- 20 @mcp.tool() registrations
|   +-- core/                  # Config, structured logging, security
|   +-- services/
|   |   +-- gemini.py          # Gemini client + generate_with_fallback()
|   |   +-- model_registry.py  # Dynamic model discovery (API + cache)
|   |   +-- openrouter.py      # OpenRouter client (OpenAI-compatible)
|   |   +-- persistence.py     # SQLite conversation storage + index
|   +-- tools/                 # Tool implementations by domain
|   |   +-- text/              # ask_gemini, ask_model, models, brainstorm, etc.
|   |   +-- code/              # analyze_codebase, generate_code
|   |   +-- media/             # image, video, TTS
|   |   +-- web/               # web_search, deep_research
|   |   +-- rag/               # file_store, file_search, upload
|   +-- schemas/               # Pydantic v2 validation
|   +-- utils/                 # @file expansion, token estimation
+-- tests/                     # Test suite (unit + integration; counts: see CLAUDE.md)
+-- .claude/
|   +-- commands/              # Slash commands
|   +-- agents/                # Subagents
+-- setup.sh                   # One-command install
+-- manifest.json              # DXT extension manifest (Claude Desktop)
+-- pyproject.toml

Security

  • Path sandboxing: all file access restricted to GEMINI_SANDBOX_ROOT
  • Secrets sanitization: API keys masked in logs (Google, AWS, GitHub, OpenAI, Anthropic, Slack, JWT, Bearer tokens)
  • XML sanitization: LLM output sanitized before parsing to prevent injection
  • Atomic file writes: automatic backups before any file modification
  • Input validation: Pydantic v2 schemas at all tool boundaries
  • Rate limiting: via provider-side quotas

Docker Deployment

bash
# Build and run
docker-compose up -d

# With log viewer (port 8080)
docker-compose --profile monitoring up -d

Docker features: non-root user, read-only filesystem with tmpfs, health check every 30s, resource limits (2 CPU, 2GB RAM), log rotation.


Troubleshooting

MCP not connecting

bash
claude mcp list           # check registration
claude mcp remove omni-ai-mcp
./setup.sh YOUR_API_KEY   # re-register
# Restart Claude Code

Import or syntax errors

bash
python3 -c "from app.core.config import config; print(f'v{config.version}')"
python3 -m pytest tests/unit/ -q

Video / Image generation timeouts

  • Video generation can take 1-6 minutes — this is normal
  • Large images (4K) take longer
  • Check your Gemini API quota at AI Studio

OpenRouter errors

  • Verify OPENROUTER_API_KEY is set and has credit
  • Check the model ID with gemini_list_models(include_openrouter=True)
  • Use the exact model ID from the list

API key update

bash
claude mcp remove omni-ai-mcp
claude mcp add omni-ai-mcp --scope user \
  -e GEMINI_API_KEY=NEW_KEY \
  -e OPENROUTER_API_KEY=NEW_OR_KEY \
  -- python3 ~/.claude-mcp-servers/omni-ai-mcp/run.py

API Costs

| Feature | Notes |

|---------|-------|

| Text generation | Free tier available · $0.075-0.30 per 1M tokens |

| Web Search | ~$14 per 1000 queries |

| File Search indexing | $0.15 per 1M tokens (one-time) |

| Image generation | Varies by resolution and model |

| Video generation | Varies by duration/resolution |

| Text-to-speech | Varies by character count |

| OpenRouter | Per-model pricing — see openrouter.ai/models |

See Google AI pricing for Gemini rates.


Development

bash
# Run tests
python -m pytest tests/unit/ -v
python -m pytest tests/integration/ -v  # requires GEMINI_API_KEY

# Quick import check
python -c "from app.core.config import config; print(f'v{config.version}')"

# Reinstall after changes
rsync -a app/ ~/.claude-mcp-servers/omni-ai-mcp/app/
# Restart Claude Code

Adding a New Tool

  1. Create app/tools/<domain>/my_tool.py with @tool(name="...", description="...", input_schema=...)
  2. Import in app/tools/<domain>/__init__.py
  3. Add Pydantic schema in app/schemas/inputs.py
  4. Write tests in tests/unit/

See CLAUDE.md for the full development guide.


Changelog

v4.4.0

  • Updated all model defaults to the latest Gemini IDs (verified live): flash → gemini-3.5-flash, flash-lite → gemini-3.1-flash-lite, image → gemini-3-pro-image / gemini-3.1-flash-image, TTS → gemini-3.1-flash-tts-preview
  • Fixed deep research: deep-research-pro-preview returned 404 NOT_FOUND → now deep-research-preview-04-2026
  • Registry fallbacks refreshed (imagen-3.0 → imagen-4.0, added veo-3.1-lite)

v4.2.0

  • /gemini-illustrate and /gemini-image commands; richer gemini_generate_image tool description

v4.1.0

  • gemini_generate_image image editing (input_images); gemini_analyze_image multi-image + media_resolution

v4.0.1

  • Fixed routing: Gemini models always use native API when key available (even if provider=openrouter)
  • Added OpenRouter fallback for Gemini text models when no Gemini key (google/ prefix)
  • Fixed Python 3.11 f-string syntax in challenge tool
  • Fixed stale unit test imports (103 -> 174 passing tests)
  • Fixed model registry: corrected flash model names (gemini-3-flash-preview, gemini-3.1-flash-lite-preview)

v4.0.0

  • ask_model: 400+ models via OpenRouter — auto-routes from model name
  • gemini_list_models: live model discovery with deprecation warnings
  • Dynamic model registry: no more hardcoded model IDs
  • PyPI distribution: pip install omni-ai-mcp
  • Claude Code plugin: slash commands + subagents
  • GitHub Actions CI/CD with Trusted Publishing

v3.3.0

  • Dual storage mode for ask_gemini: local (SQLite) or cloud (Interactions API, 55-day retention)
  • gemini_list_conversations, gemini_delete_conversation
  • Cross-platform file locking

v3.2.0

  • gemini_deep_research: autonomous multi-step research (5-60 min, 40+ sources)

v3.0.0

  • FastMCP migration, SQLite persistence, security hardening

Contributing

Contributions are welcome! Open an issue or pull request on GitHub.


License

MIT — see LICENSE

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Server Information

Source
GITHUB
Language
other
License
MIT
Transport
STDIO
Added
Aug 11, 2026
Updated
Oct 1, 2026