TrueFoundry Connector for AI agents.
8 live capabilities
Deploy and manage LLM infrastructure from a single unified gateway.
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Why people use TrueFoundry
TrueFoundry for Unified LLM Infrastructure Management
TrueFoundry MCP cleans this up by acting as a single point of entry. Instead of jumping between capabilities, your AI client talks to one gateway. It handles the routing, security, and metrics, giving you a single plane to manage your entire model fleet.
What Vinkius changes
You get a single gateway that hides the complexity of multiple model providers and infrastructure setups.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Switching providers due to price hikes
A Platform Engineer needs to move from one LLM provider to another because of a price hike.
- Real-world use case 02
Deploying capabilities without managing servers
A developer wants to deploy a new MCP capability but doesn't want to manage the underlying server.
- Real-world use case 03
Identifying bottlenecks in production
A team is hitting rate limits on their primary model.
Complete set · 8capabilities
The complete TrueFoundry capability set.
These are the exact actions your AI can choose when you ask it to work with TrueFoundry.
01—04
4 capabilities in this set.
Part of 8 available through TrueFoundry.
- 01 Capability
Truefoundry deploy mcp server
Start a new backend container process using the TrueFoundry service mesh. Use this to spin up new capabilities on your infrastructure.
- 02 Capability
Truefoundry generate embeddings
Create semantic vectors using a single, unified abstraction layer. This keeps your embedding logic consistent across all apps.
- 03 Capability
Truefoundry get deployment status
View detailed metrics and status for your orchestration matrix. It helps you see real-time usage and health.
- 04 Capability
Truefoundry get mcp server info
Get the specific JSON metadata for a registered TrueFoundry capability. This is useful for inspecting capability schemas.
05—08
4 capabilities in this set.
Part of 8 available through TrueFoundry.
- 05 Capability
Truefoundry list deployments
See all the backend topologies currently running for your team. Use this to keep track of your active services.
- 06 Capability
Truefoundry list gateway models
See every foundation model available through the unified AI gateway. It shows you exactly what's accessible.
- 07 Capability
Truefoundry list mcp servers
Get a full registry mapping of all available MCP capabilities in your environment. This gives you a bird's eye view of your capabilities.
- 08 Capability
Truefoundry run gateway chat
Send a chat query through the gateway while keeping your original keys isolated. This handles the routing for you.
Set up in minutes
One URL. Then ask TrueFoundry to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use TrueFoundry from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_f00nYwHsDWFv4EirgRZbXCnvKYC62empWE9xeumU/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it TrueFoundry, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable TrueFoundry for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_f00nYwHsDWFv4EirgRZbXCnvKYC62empWE9xeumU/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the TrueFoundry URL.
- Step 03
Save and start
Save the connection and enable TrueFoundry in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"truefoundry": {
"url": "https://edge.vinkius.com/vk_preview_f00nYwHsDWFv4EirgRZbXCnvKYC62empWE9xeumU/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using TrueFoundry
Open Agent mode in chat and ask: "Using TrueFoundry, help me...". 8 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"truefoundry": {
"url": "https://edge.vinkius.com/vk_preview_f00nYwHsDWFv4EirgRZbXCnvKYC62empWE9xeumU/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using TrueFoundry
Ask Copilot: "Using TrueFoundry, help me...". 8 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"truefoundry": {
"url": "https://edge.vinkius.com/vk_preview_f00nYwHsDWFv4EirgRZbXCnvKYC62empWE9xeumU/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using TrueFoundry
Open Cascade and ask: "Using TrueFoundry, help me...". 8 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"truefoundry": {
"url": "https://edge.vinkius.com/vk_preview_f00nYwHsDWFv4EirgRZbXCnvKYC62empWE9xeumU/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using TrueFoundry
Ask Cline: "Using TrueFoundry, help me...". 8 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add truefoundry --transport http "https://edge.vinkius.com/vk_preview_f00nYwHsDWFv4EirgRZbXCnvKYC62empWE9xeumU/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using TrueFoundry
Ask Claude: "Using TrueFoundry, show me...". 8 tools are ready
Where the request belongs
Work TrueFoundry can move forward.
This is for the platform engineer tired of manual scaling, the AI engineer who needs to swap models without rewriting code, and the software architect building a secure company-wide AI plane.
Platform Operations Engineer
Monitors deployment metrics and manages container scaling to ensure high availability for internal AI capabilities.
AI Engineer
Tests different foundation models and manages embedding workflows without hardcoding multiple API keys.
Software Architect
Designs a unified gateway to provide secure, governed access to LLMs across the entire organization.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsLiteLLM (LLM Proxy & Spend Tracking)
Manage your LLM gateway via LiteLLM. generate API keys, track spending, and orchestrate model fallback paths.
Portkey
AI gateway observability: monitor logs, costs, and manage LLM configurations via agents.
Keywords AI
Monitor and optimize your LLM API usage with a unified gateway that tracks costs, latency, and model performance across providers.
Hugging Face LLM
Connect Hugging Face LLM to any AI agent via MCP.
NVIDIA API Catalog
Cloud Engine proxy running native foundational completions natively utilizing active Nemotron and Llama3 architectures.
Groq
Run large language models at unprecedented speed with custom LPU hardware that delivers real-time AI inference at massive scale.
Bring your own AI
Change the model, client or framework. Keep TrueFoundry connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about TrueFoundry.
The practical details behind the request, access and result.
How does TrueFoundry help me manage multiple LLMs?
It provides a unified gateway that routes your requests to different providers. You only need to connect your AI client to one endpoint instead of managing separate keys and configurations for every model.
Can I use TrueFoundry to deploy my own Connector capabilities?
Yes, the Connector allows you to deploy new backend container processes directly onto your infrastructure. This lets you manage your entire capability topology from one place.
Does this help with LLM rate limits?
Yes, by using the gateway, you can monitor usage metrics and status in real-time. This helps you see exactly how much capacity you have left across your different providers.
Can I use it for embeddings?
Yes, it includes a unified abstraction for generating embeddings. This ensures that your text-to-vector logic stays consistent across all your different applications.
Is TrueFoundry MCP good for production environments?
It's specifically designed for production. It handles the orchestration, security, and monitoring that teams need to run reliable AI infrastructure at scale.
What happens to my API keys when I use this?
Your original vendor keys stay isolated. The Connector routes your requests through the TrueFoundry proxy, so your core codebase doesn't have to handle multiple keys directly.
Can I route conversational streams directly via the AI agent using the Universal Gateway?
Yes! You can orchestrate inferences parsing run_gateway_chat providing dedicated string formats mapping natively any enabled model.
Is it possible to monitor crashed services or container states?
Absolutely. Target the instance ID and emit get_deployment_status explicitly bounding execution limits and fetching live log matrices.
Are the deployment configuration variables isolated upon server launch?
Yes, using deploy_mcp_server dynamically provisions encapsulated boundaries. You stringify environment tokens seamlessly obscuring values into active runtimes only.
One connection away
Give your agent a direct line to TrueFoundry.
Connect TrueFoundry once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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