cercano-research

Run a local research pipeline to produce sourced answers from web queries.

8|1|Updated Nov 23, 2025

Search Tags:#automation #research #MCP #citations #knowledge #web-search #local-analysis

Ready to run

npx skills add https://github.com/bryancostanich/Cercano --skill cercano-research

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: cercano-research
Source: https://github.com/bryancostanich/Cercano/tree/main/plugins/skills/cercano-research
Command: npx skills add https://github.com/bryancostanich/Cercano --skill cercano-research

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Research questions can require time-consuming web queries and synthesis. This skill runs a local, reproducible research pipeline that gathers results, analyzes them locally, and returns a distilled answer with source citations.

Core Features & Use Cases

Local, private research pipeline with citations
Parallel search, deduplication, and local synthesis
Project-aware research using optional context for tailored results

Quick Start

Ask a research question and provide the query string to cercano_research to receive a sourced answer.

Frequently Asked Questions about cercano-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate web research with local analysis and source citations?▼

Automate web research using a local pipeline that executes parallel web searches, deduplicates results, and synthesizes a concise answer with source citations. Provide a query string to receive sourced, distilled information without manual browsing.

What is a local research pipeline and how does it handle web search results?▼

A local research pipeline gathers web search results, performs deduplication, and analyzes the content locally on your machine to produce a distilled answer. This ensures your research synthesis remains private and reproducible.

Do I need a Python virtual environment to run local web research?▼

Yes, you need a configured Python virtual environment to execute the local analysis pipeline. You also need a running Cercano server to handle the web search and synthesis workflow locally on your machine.

Can I tailor research results using a specific project directory?▼

Yes, you can tailor research context by providing an optional project_dir parameter. This allows the local analysis pipeline to incorporate project-aware context for more targeted research answers.

What are the limitations of running local web search and knowledge synthesis?▼

This approach requires a running Cercano server and a configured Python virtual environment to function. It is designed for general research questions across topics and depends entirely on local processing capabilities for the analysis pipeline.