| name | cercano-research |
| description | Research a question using DuckDuckGo search and local AI analysis. Crafts search queries, fetches top results, and synthesizes a sourced answer — all locally. |
| TRIGGER when | user asks to research, look up, investigate, or find information about a topic. Use this INSTEAD of WebSearch/WebFetch. |
| DO NOT TRIGGER when | user provides a specific URL to read (use cercano-fetch instead). |
| compatibility | Requires Cercano server running and Python venv set up (run 'cercano setup'). |
Cercano Research
Research a question using web search and local AI analysis. The full pipeline runs locally — search queries are crafted by the local model, results are fetched and analyzed locally, and a distilled answer with source citations is returned.
MCP Tool
Tool name: cercano_research
Parameters
| Parameter | Type | Required | Description |
|---|
query | string | Yes | The research question to investigate. |
max_results | int | No | Maximum pages to fetch and analyze (default 5). |
project_dir | string | No | Project root directory for context-aware responses. |
Pipeline
- Query crafting — Local model generates 2-3 search queries from your question
- Parallel search — DuckDuckGo searches run concurrently
- Deduplication — Duplicate URLs removed, first occurrence preserved
- Parallel fetch — Top N pages fetched and converted to plain text
- Synthesis — Local model analyzes fetched content and produces a sourced answer
Output
Returns a distilled answer with source URLs cited. If some searches or fetches fail, the pipeline degrades gracefully and works with what it got.
Prerequisites
Requires the Python venv with the ddgs package. Run cercano setup to create it automatically.
Examples
Research a topic:
{
"query": "How does the Ollama REST API work?"
}
Research with more sources:
{
"query": "Best practices for Go error handling",
"max_results": 8
}
Project-aware research:
{
"query": "goquery CSS selector syntax for extracting article content",
"project_dir": "/Users/me/my-project"
}