from agno.agent import Agentfrom agno.tools.mcp import MCPToolsfrom agno.models.anthropic import Claude
async with MCPTools(command="uv run --with mcp-clickhouse --python 3.13 mcp-clickhouse", env=env, timeout_seconds=60) as mcp_tools: agent = Agent( model=Claude(id="claude-3-5-sonnet-20240620"), markdown=True, tools = [mcp_tools] )await agent.aprint_response("What's the most starred project in 2025?", stream=True)
Response
▰▱▱▱▱▱▱ Thinking...┏━ Message ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓┃ ┃┃ What's the most starred project in 2025? ┃┃ ┃┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛┏━ Tool Calls ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓┃ ┃┃ • list_tables(database=github, like=%) ┃┃ • run_select_query(query=SELECT ┃┃ repo_name, ┃┃ SUM(count) AS stars_2025 ┃┃ FROM github.repo_events_per_day ┃┃ WHERE event_type = 'WatchEvent' ┃┃ AND created_at >= '2025-01-01' ┃┃ AND created_at < '2026-01-01' ┃┃ GROUP BY repo_name ┃┃ ORDER BY stars_2025 DESC ┃┃ LIMIT 1) ┃┃ ┃┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛┏━ Response (34.9s) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓┃ ┃┃ To answer your question about the most starred project in 2025, I'll need to query the ClickHouse database. ┃┃ However, before I can do that, I need to gather some information and make sure we're looking at the right data. ┃┃ Let me check the available databases and tables first.Thank you for providing the list of databases. I can see ┃┃ that there's a "github" database, which is likely to contain the information we're looking for. Let's check the ┃┃ tables in this database.Now that we have information about the tables in the github database, we can query the ┃┃ relevant data to answer your question about the most starred project in 2025. We'll use the repo_events_per_day ┃┃ table, which contains daily event counts for each repository, including star events (WatchEvents). ┃┃ ┃┃ Let's create a query to find the most starred project in 2025:Based on the query results, I can answer your ┃┃ question about the most starred project in 2025: ┃┃ ┃┃ The most starred project in 2025 was deepseek-ai/DeepSeek-R1, which received 84,962 stars during that year. ┃┃ ┃┃ This project, DeepSeek-R1, appears to be an AI-related repository from the DeepSeek AI organization. It gained ┃┃ significant attention and popularity among the GitHub community in 2025, earning the highest number of stars ┃┃ for any project during that year. ┃┃ ┃┃ It's worth noting that this data is based on the GitHub events recorded in the database, and it represents the ┃┃ stars (WatchEvents) accumulated specifically during the year 2025. The total number of stars for this project ┃┃ might be higher if we consider its entire lifespan. ┃┃ ┃┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛