wellread

The deeper your session, the more expensive research gets - and the more wellread saves.

- Your agent researches every technical question from scratch. When it doesn't, it hallucinates - outdated APIs, wrong examples, broken code.
- Every turn re-sends the whole conversation. By turn 100, you've paid for the same context a hundred times.

Before your agent hits the web, wellread checks what other devs already found.

- Hit→ instant answer from verified sources. Zero web searches. One turn.
- Partial→ starts from what exists, only researches the gaps.
- Miss→ normal research, then saves the summary for whoever comes next.

Your agent doesn't just spend fewer tokens. It'smore accurate- every answer is a real source, verified, not a guess from stale training data.

Update:npx wellread@latest-Uninstall:npx wellread uninstall

You don't need a crowd for wellread to pay off.

Singleplayer- your own research comes back to you. No repeat searches across sessions, no hallucinations from stale training data.

Multiplayer- when another dev has already cracked that Auth.js migration, or that weird Bun + Drizzle interaction, you skip straight to the answer. One person researches, everyone benefits.

Early users build the network. Their contributions get credited - and permanent.

Each entry knows how fast its topic changes:

When an agent re-verifies, the clock resets for everyone.

Six layers between your private context and the shared network:
- Hook instruction- before anything leaves your machine, the hook tells your agent to sanitize the query: strip project names, API keys, file paths, credentials. Only the generic technical concept is sent.
- Search schema- the search tool's parameter description reinforces: "Remove project names, API keys, file paths, credentials."
- Save schema- the save tool explicitly says: "NEVER include project/repo/company names, internal URLs, file paths, credentials, business logic. Content is PUBLIC."
- URL gate (server, hard reject)- every source must start withhttps://orhttp://. File paths, library identifiers, internal URLs → rejected. The contribution is not saved.
- Path detection (server, hard reject)- the server scans content and search surface for local paths (/Users/...,/home/...,file://,C:\...). If found → rejected.
- By design- your agent doesn't forward your input. It synthesizes from public sources. What gets saved is a distilled summary of public docs, not your code or conversation.

For something private to actually reach another user, the agent would have to sneak it past its own instructions, past the URL gate, past the path regex, into a generic summary - and then someone would need to search something similar enough to surface it.

See your token savings, your top contributions, and how many devs used research you saved.

Works with any MCP client. Best experience with Claude Code. Also supports Cursor, Windsurf, Gemini CLI, VS Code, OpenCode.

Search global news using natural language. Webz.io News Search API returns the most relevant articles and content, with filters for source, country, language, date, sentiment, and category.

A self-hosted MCP server that indexes documentation from various sources and serves it to AI Agents with semantic search.

Multimodal RAG for source-backed AI answers

A private, local research "second brain" for Claude — cited answers from your own library (it won't invent what it can't find), persistent project memory, daily briefs, a live meeting assistant, and 34 specialist agents. Runs entirely on your machine.

Cited compliance, legal & security intelligence for AI agents — 300+ law, regulation and standards corpora (GDPR, NIS2, AI Act, DORA) with article-level citations, plus live CVE/KEV/EPSS vulnerability context. OAuth remote server, free tier

Lightning-Fast, High-Accuracy Deep Research Agent 👉 8–10x faster 👉 Greater depth & accuracy 👉 Unlimited parallel runs

RAG Search over your content powered by Inkeep

Provides AI assistants with direct access to Mastra.ai's complete knowledge base.

Production-ready RAG out of the box to search and retrieve data from your own documents.

Free local RAG for Claude Code - Save tokens & time with vector search. Indexes markdown docs and finds relevant info without reading entire files (40x fewer tokens, 15x faster).