> For the complete documentation index, see [llms.txt](https://docs.allmcp.co/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.allmcp.co/documentation/agent-frameworks/lmstudio.md).

# LM Studio

LM Studio is a local LLM server — it serves models but does not consume MCP tools directly. To use AllMCP with an LM Studio model, pair it with a framework that supports both a custom LLM backend and MCP.

{% hint style="info" icon="link" %}
**LM Studio exposes an OpenAI-compatible API on `http://localhost:1234`.** Point any OpenAI-compatible client at it and connect that client's agent to AllMCP for tools.
{% endhint %}

***

## Pick your framework

Both approaches keep the LLM local in LM Studio while AllMCP serves the tools remotely. Choose the one that matches the framework you already use.

{% tabs %}
{% tab title="LangChain (recommended)" %}
**Recommended approach: LangChain + LM Studio + AllMCP**

{% code title="install" %}

```bash
pip install langchain-mcp-adapters langchain-openai langgraph
```

{% endcode %}

{% code title="agent.py" overflow="wrap" %}

```python
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent


async def main():
    client = MultiServerMCPClient({
        "allmcp": {
            "url": "https://go.allmcp.co/mcp/",
            "transport": "streamable_http",
            "headers": {"X-API-Key": "YOUR_API_KEY"},
        }
    })
    tools = await client.get_tools()

    # LM Studio's OpenAI-compatible endpoint
    llm = ChatOpenAI(
        base_url="http://localhost:1234/v1",
        api_key="lm-studio",  # any non-empty string
        model="local-model",  # matches the model loaded in LM Studio
    )

    agent = create_react_agent(llm, tools)

    result = await agent.ainvoke({
        "messages": [{"role": "user", "content": "List my Bitrix24 contacts"}]
    })
    print(result["messages"][-1].content)


asyncio.run(main())
```

{% endcode %}
{% endtab %}

{% tab title="PydanticAI" %}
**PydanticAI + LM Studio + AllMCP**

{% code title="agent.py" overflow="wrap" %}

```python
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP
from pydantic_ai.models.openai import OpenAIModel
from openai import AsyncOpenAI

lm_studio_client = AsyncOpenAI(
    base_url="http://localhost:1234/v1",
    api_key="lm-studio",
)
model = OpenAIModel("local-model", openai_client=lm_studio_client)

allmcp = MCPServerStreamableHTTP(
    url="https://go.allmcp.co/mcp/",
    headers={"X-API-Key": "YOUR_API_KEY"},
)

agent = Agent(model, toolsets=[allmcp])
```

{% endcode %}
{% endtab %}
{% endtabs %}

***

## Model tips

{% hint style="warning" icon="sparkle" %}
**Enable a model that supports tool/function calling in LM Studio:**

* Models tagged with `[Tool Use]` in the LM Studio model browser work best
* Look for Llama 3.2 Instruct, Qwen 2.5 Instruct, or Mistral Nemo Instruct
* Enable **Grammar** mode for more reliable JSON output in tool calls
  {% endhint %}

{% hint style="info" %}
AllMCP always runs remotely at `https://go.allmcp.co/mcp/`. Only the LLM runs locally via LM Studio. Your provider connections live in AllMCP, so once you connect a provider its tools are available to any client you point at the endpoint.
{% endhint %}

***

## See also

{% content-ref url="/pages/uBaUeZYQpupBMd5c1BY0" %}
[Overview](/documentation/agent-frameworks/frameworks.md)
{% endcontent-ref %}

<table data-view="cards"><thead><tr><th></th><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><h4><i class="fa-table-cells" style="color:$primary;">:table-cells:</i></h4></td><td><strong>Browse providers</strong></td><td>See every provider you can connect and the tools each one offers.</td><td><a href="https://docs.allmcp.co/documentation/providers">https://docs.allmcp.co/documentation/providers</a></td></tr></tbody></table>


---

# Agent Instructions
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