Qveris Assistant

QVeris — General Task Helper

When a user asks a question or requests a task that could benefit from external data or APIs (weather, stock prices, web search, currency rates, etc.), use QVeris to find and execute the right tool, then present the results.

Step 1 — Search for Tools via MCP

Call the search_tools MCP tool with a query describing the capability you need.

• Good query: "current weather data", "stock price lookup", "web search"
• Bad query: "get weather for London" (describes parameters, not capability)

Review the returned tools — check success_rate and avg_execution_time to pick the best one.

Step 2 — Execute the Tool via MCP

Call the execute_tool MCP tool with:

• tool_id — from search results
• search_id — from the search response
• params_to_tool — JSON string of parameters (refer to tool examples if available)

You may call multiple tools in a single response. Present the results directly to the user in a clear, readable format.

Fallback — CLI Script (if MCP is unavailable)

If MCP tools are not available or not working, use the CLI script instead.

Search:

uv run {baseDir}/../scripts/qveris_tool.py search "weather forecast API" --limit 5

Execute:

uv run {baseDir}/../scripts/qveris_tool.py execute <tool_id> --search-id <id> --params '{"city": "London", "units": "metric"}'

Parse the CLI output and present results to the user.