How to Use the AI Token Counter MCP in AutoGen

Q: Can different agents in an AutoGen setup use the AI Token Counter?

Yes. Once you add the MCP tool to your AssistantAgent configuration, any agent in the group with tool-calling capabilities can use it. You could have a 'Planner' agent check its own output size or a 'Critic' agent check the Planner's verbosity.

Q: What's the process for adding the AI Token Counter to an AutoGen project?

Install autogen-extmcp, then use the mcpservertools function with your Vinkius server URL to fetch the tool definitions. You pass this list of tools directly to your AssistantAgent when you create it.

Let your AutoGen agents debate context limits, not just crash into them. Add token-awareness to your multi-agent conversations.

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Setup AI Token Counter with AutoGen

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Build a "Context Guardian" Agent

In an AutoGen system, you can create a specialized agent whose only job is to manage the conversation's context. This "guardian" agent would use the `count_tokens` tool to monitor the size of the shared message history. When the context approaches the LLM's limit, the guardian can interject, instructing other agents to summarize their points or proposing a reset. This prevents the entire conversation from collapsing due to a token overflow error.

Smarter Tool-Using Agents

When an AutoGen agent calls an external tool that returns a large block of text, it can't just dump that into the group chat. Doing so could instantly exhaust the context window for all participating agents. With this MCP, the agent can first call the external tool, then use the token counter to check the size of the output. Based on the count, it can provide a summary or a link, keeping the main conversation clean.

Enable Negotiation with an MCP Server

AutoGen's power comes from agent negotiation. The resource manager agent can use this MCP Server to count the tokens in a proposed plan and push back, saying "That's too long, it will break our context. Summarize it." This creates a dynamic where agents don't just solve a problem; they solve it within constraints. It moves your multi-agent system from a simple script to a more realistic, resource-aware collaboration.

Setup guide

Set up AI Token Counter MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes AI Token Counter tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="AI Token Counter_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent AI Token Counter data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="AI Token Counter_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent AI Token Counter data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by GPT Tokenizer. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about AI Token Counter MCP in AutoGen

It gives an agent the ability to count tokens in the conversation history. Before the history gets too long, that agent can trigger a summarization action, keeping the chat from hitting the API's context limit.

Yes. Once you add the MCP tool to your `AssistantAgent` configuration, any agent in the group with tool-calling capabilities can use it. You could have a 'Planner' agent check its own output size or a 'Critic' agent check the Planner's verbosity.

Install `autogen-ext[mcp]`, then use the `mcp_server_tools` function with your Vinkius server URL to fetch the tool definitions. You pass this list of tools directly to your `AssistantAgent` when you create it.

Definitely. An agent generating code can use the token counter to check the length of its proposed file. This is useful for ensuring the generated code block fits within chat limits or other platform constraints.

The only data this MCP touches is the text string sent for tokenization. This data is processed in a sandboxed, in-memory environment and is never persisted. Vinkius provides a cryptographically signed audit log for every call, but the input text itself is ephemeral.

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