Compatible with every major AI agent and IDE
What is the LocalAI MCP Server?
Connect your LocalAI instance to any AI agent and leverage powerful multimodal capabilities directly from your own infrastructure.
What you can do
- Text Generation — Use
chat_completionsoranthropic_messagesto generate text using local models with full OpenAI or Anthropic compatibility. - Image Synthesis — Create visual content from text prompts using the
generate_imagetool, supporting custom sizes and negative prompts. - Audio Processing — Convert speech to text with
transcribe_audioor generate natural-sounding speech from text usingtext_to_speech. - Advanced Search & RAG — Generate vector embeddings with
create_embeddingsand improve search relevance using thererank_documentstool. - Computer Vision — Analyze images and identify elements using the
detect_objectstool. - System Management — Monitor your instance with
list_models,get_system, andgetVersionto ensure optimal performance.
How it works
- Subscribe to this server
- Provide your LocalAI Base URL (e.g.,
http://localhost:8080) and optional API Key - Start interacting with your local models through Claude, Cursor, or any MCP client
Who is this for?
- Privacy-Conscious Developers — Run powerful AI workflows without sending sensitive data to third-party cloud providers.
- AI Researchers — Easily test and swap different local models for chat, vision, and audio tasks.
- DevOps Engineers — Integrate local AI capabilities into internal tools and automated pipelines.
Built-in capabilities (19)
Generate messages (Anthropic compatible)
Install a model from the gallery
Generate chat completions (OpenAI compatible)
Create text embeddings
Detect objects in an image
Analyze face demographics
Identify faces (1:N)
Enroll a face into the store
Verify faces (1:1)
Supports negative prompts using | separator. Generate images from text prompts
Check authentication state and providers
View personal token usage
View system and backend info
Get LocalAI version
List available models
Generate open responses
Rerank documents based on a query
Convert text to audio (TTS)
Pass the file data or path as required by your LocalAI setup. Transcribe audio to text
Why Google ADK?
Google ADK natively supports LocalAI as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 19 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
- —
Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
- —
Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with LocalAI
- —
Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
- —
Seamless integration with Google Cloud services means you can combine LocalAI tools with BigQuery, Vertex AI, and Cloud Functions
LocalAI in Google ADK
LocalAI and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect LocalAI to Google ADK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for LocalAI in Google ADK
The LocalAI MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 19 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Google ADK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
LocalAI for Google ADK
Every tool call from Google ADK to the LocalAI MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I see which AI models are currently installed on my LocalAI server?
You can use the list_models tool. It will return a complete list of all available models on your instance, including their IDs and capabilities.
Does this server support generating images locally?
Yes! By using the generate_image tool, you can provide a prompt and optional size to generate images directly on your hardware using supported models like Stable Diffusion.
Can I use this to transcribe audio files into text?
Absolutely. The transcribe_audio tool allows you to send audio data or file paths to your LocalAI instance for high-quality transcription using models like Whisper.
How does Google ADK connect to MCP servers?
Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.
Can ADK agents use multiple MCP servers?
Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.
Which Gemini models work best with MCP tools?
Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.
McpToolset not found
Update: pip install --upgrade google-adk
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