Give Your Agent Free Unlimited Research with Pi Research

Where this fits

You're building an agent that needs to answer questions about fast-moving topics—pricing pages, API docs, competitor news—but your current tooling either hits paywalls, throttles your requests, or forces you to manually curate sources. Pi Research solves that by giving your agent a free, unlimited web search and a built-in knowledge store, so it can pull fresh facts and remember them across sessions without you wiring up a separate database.

Why agents benefit

• Unlimited, free search – No API key, no quota errors, no cost spikes. Your agent can run dozens of queries per task without anxiety.
• Persistent knowledge store – Search results are automatically cached, so repeat queries are instant and your agent builds a growing memory of past research.
• Safe scraping – Built-in rate limiting, freshness controls, and a “smart” scraper that extracts readable content from messy HTML (including PDFs and paywalled pages).
• Installable as a skill – Drop it into any agent framework (Claude, LangChain, custom) via a single npx command; it exposes clean, typed tools for search and store operations.
• Structured results – Returns JSON with titles, snippets, URLs, and timestamps, making it easy to parse and act on instead of wrestling with raw HTML.

Practical scenarios

Competitive pricing monitor

Your agent runs a weekly job to compare three SaaS pricing pages. Pi Research searches each domain, scrapes the current plans, and stores the results in its knowledge store. Next week, it only fetches changed pages and gives you a diff—no re-crawling everything.

Research assistant for a content team

Your agent helps writers fact-check. You ask it to “verify these five claims about renewable energy.” It searches broadly, saves the best sources into the store, and returns a citation-ready summary. The store persists, so the next request about a related claim reuses prior findings.

Live support bot with context

A support bot uses Pi Research to look up product docs during a chat. When a user asks about a feature, the bot searches, stores the relevant page, and answers precisely. If the same question pops up later, the bot answers from cache instantly.

Add it to your agent workflow

Install the skill in your agent project:

npx skills add Lincoln504/pi-research

Then, in your agent code, import and call the search tool. Minimal example:

import { search } from '@lincoln504/pi-research';

const results = await search('latest pricing for OpenAI API');
console.log(results.summary); // first paragraph from top result
console.log(results.sources); // list of {url, title, snippet, accessedAt}

Optionally, enable the knowledge store to cache results automatically—check docs/KNOWLEDGE-STORE.md for configuration. The skill also exposes store.get and store.put for manual control.

Compare before adopting

Before committing, compare Pi Research against alternatives like Tavily, Serper, or building your own scraper. Evaluate: quality signals – check GitHub Issues, recent commits, and whether the author responds to feedback; maintenance freshness – the repo is under active development (28 stars, recent CI green), but verify it hasn't stalled; alternatives – free search tools exist, but Pi Research bundles a knowledge store, which most don't; workflow fit – does it integrate with your agent framework? The skill is framework-agnostic, but test its tool definitions against your agent's parsing. Finally, read honest community reviews (e.g., on OpenAgentSkill) to see if anyone hit edge cases with scraping or storage.

Why it is worth tracking

Pi Research is worth watching because it tackles a common pain point—free, unlimited research without API keys—and does it with a thoughtful architecture (agent skill + SDK + storage). The 28 stars are modest, but the codebase is clean, documented, and MIT-licensed; the author is actively releasing updates. If your agent relies on external facts, this skill could save you money and dev time. Evaluate it now, and keep an eye on its GitHub for new features like multi-provider fallback or advanced caching. The project is young, but its design philosophy—smart, safe, and free—fits the open-source agent ecosystem well. For a detailed breakdown and community feedback, check the skill page on OpenAgentSkill.