How to Use the Bitquery (Web3 Blockchain GraphQL APIs) MCP in AutoGen

Q: How do AutoGen agents share Bitquery (Web3 Blockchain GraphQL APIs) credentials?

One agent runs generatetoken to fetch the active credential. Once retrieved, the token is shared in the group chat context so other agents can run queryv1 and queryv2.

Q: How do agents handle Bitquery (Web3 Blockchain GraphQL APIs) syntax errors in AutoGen?

If queryv1 returns a GraphQL syntax error, the execution agent passes the error back to the group. A developer agent then rewrites the query and executes it again.

Let AutoGen agents debate and execute complex blockchain GraphQL queries across 40+ chains.

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Connect Bitquery (Web3 Blockchain GraphQL APIs) MCP to AutoGen

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Setup Bitquery (Web3 Blockchain GraphQL APIs) with AutoGen

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Run multi-agent debates with this MCP Server

This MCP Server allows your AutoGen agents to collaborate on complex on-chain investigations using `query_v1` and `query_v2`. One agent can fetch raw transaction data while another validates the query structure before execution. This setup eliminates syntax errors in your GraphQL queries. The agents debate the best filters for DexTrades or BalanceUpdates before hitting the live API.

Manage API credentials via AutoGen agent collaboration

The `generate_token` tool gives your agents the ability to refresh credentials autonomously when session limits are reached. A coordinator agent detects authorization errors and instructs the auth agent to run the token generator. This keeps your multi-agent conversations running without human intervention. The new token is instantly shared among all active agents in the group chat.

Analyze live block data with dedicated AutoGen agents

Use `query_v2` with this MCP Server to feed live streaming blockchain events into your agent conversations. A security agent can monitor incoming Calls and Events, while a trading agent watches DexTradesByTokens to spot market anomalies. The agents discuss these real-time updates to reach a consensus on market trends. This distributed analysis happens entirely within your configured AutoGen group chat.

Setup guide

Set up Bitquery (Web3 Blockchain GraphQL APIs) 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 Bitquery (Web3 Blockchain GraphQL APIs) 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="Bitquery (Web3 Blockchain GraphQL APIs)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Bitquery (Web3 Blockchain GraphQL APIs) data")
print(result.messages[-1].content)

Get your connection token →

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="Bitquery (Web3 Blockchain GraphQL APIs)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Bitquery (Web3 Blockchain GraphQL APIs) 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 Bitquery. 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 Bitquery (Web3 Blockchain GraphQL APIs) MCP in AutoGen

One agent runs `generate_token` to fetch the active credential. Once retrieved, the token is shared in the group chat context so other agents can run `query_v1` and `query_v2`.

Yes, the adapter translates the tools for all agents in your group. They can concurrently call `query_v1` for historical metrics and `query_v2` for live stream data.

If `query_v1` returns a GraphQL syntax error, the execution agent passes the error back to the group. A developer agent then rewrites the query and executes it again.

Yes, you can connect the server using Streamable HTTP transport. This allows your distributed agents to query the blockchain from different runtime environments.

Your Client ID and Secret are never exposed to the LLM. The token generation happens via `generate_token` within a secure, isolated Vinkius MCP sandbox that keeps your raw credentials hidden from the agent conversation logs.

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