How to Use the Moonriver (Moonriver Block Explorer API) MCP in AutoGen
Let your AutoGen agents debate and verify Moonriver transactions and blocks in real time.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Moonriver (Moonriver Block Explorer API) MCP to AutoGen
Create your Vinkius account to connect Moonriver (Moonriver Block Explorer API) to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Verify transactions via multi-agent debate
Use `get_extrinsic` and `list_extrinsics` to retrieve raw transaction details and let your AutoGen agents analyze them from different angles. One agent checks the transaction status while another verifies the gas parameters. This collaborative check ensures that your system never acts on unconfirmed or suspicious transactions. The agents debate the extrinsic state until they reach a consensus.
Track transfers with this AutoGen MCP Server
Use `list_transfers` to feed transfer logs directly into your multi-agent conversations. A compliance agent can flag large volume moves while a portfolio agent updates asset valuations simultaneously. This parallel processing model handles complex financial workflows without bottlenecking your main application logic. The agents coordinate their tool usage to build a complete picture of account activity.
Fetch runtime metadata for network configuration checks
Use `get_metadata` to retrieve the current Moonriver runtime spec and let your agents verify network parameters before executing transactions. This prevents your system from submitting incompatible payloads to the chain. Your agents use this data to dynamically adjust their behavior based on the active runtime version. They run these checks autonomously in the background, keeping your deployment stable.
Set up Moonriver (Moonriver Block Explorer API) 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Moonriver (Moonriver Block Explorer API) tools and returns structured results.
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="Moonriver (Moonriver Block Explorer API)_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Moonriver (Moonriver Block Explorer API) data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Moonriver (Moonriver Block Explorer API)_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Moonriver (Moonriver Block Explorer API) data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Moonriver. 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 Moonriver (Moonriver Block Explorer API) MCP in AutoGen
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