BrowseAI Dev

io.github.BrowseAI-HQPublished by GitHub account BrowseAI-HQv0.4.0Updated Oct 27, 2026

Evidence-backed web research for AI agents with citations and confidence scores.

Overview

AI-generated overview

BrowseAI Dev (lastsearch) is a local MCP server that gives an assistant real-time web search with cited, evidence-verified answers and confidence scores.

What you can do
  • Search the web across multiple providers and fetch pages as clean text
  • Extract structured claims from pages and verify them against source quotes
  • Produce full cited answers with confidence scores, contradiction detection and fast, thorough or deep depth modes
  • Compare a raw model answer against an evidence-backed one, and run an anti-hallucination answer engine
  • Create, query, recall, export, share and fork persistent research sessions
  • Submit accuracy feedback on results
When to use it
Useful when an assistant needs current, source-backed research rather than model memory: fact-checking, literature or market comparisons, and multi-step investigations where citations and confidence matter. Also fits agents that want to accumulate research across several questions in a session.
Requirements
Runs locally via npx (Node.js) over stdio, or as an HTTP server with a configurable port. Requires a BrowseAI Dev API key supplied in the BROWSE_API_KEY environment variable; the README also refers to a LastSearch key for premium features. Network access is needed for search and page fetching.
Before you install
The API key is a secret passed in an environment variable and is required for all tool calls. Queries, page fetches and extracted content go to the provider's service and its search, parsing and model partners. Deep mode costs three times the quota and is capped per day. Sessions can be shared publicly, returning a share URL, so check what a session contains before sharing.

Installation

In SourceWeft

  1. Open BrowseAI Dev in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

lastsearch

Reliable research infrastructure for AI agents. The research layer your agents are missing.

MCP server with real-time web search, evidence extraction, and structured citations. Drop into Claude Desktop, Cursor, Windsurf, LangChain, CrewAI, or any agent pipeline.

What it does

Instead of letting your AI hallucinate, lastsearch gives it real-time access to the web with structured, cited answers:

Your question → Web search → Neural rerank → Fetch pages → Extract claims → Verify → Cited answer (streamed)

Every answer includes:

  • Claims with source URLs, verification status, and consensus level
  • Evidence-based confidence score (0-1), not LLM self-assessed, auto-calibrated from feedback
  • Source quotes verified against actual page text
  • Atomic claim decomposition — compound facts split and verified independently
  • Execution trace with timing
  • 3 depth modes — "fast" (default), "thorough" (auto-retry with rephrased queries), "deep" (premium multi-step agentic research: iterative think-search-extract-evaluate cycles with gap analysis, up to 4 steps, targets 0.85 confidence — requires LastSearch key + sign-in, 3x quota cost, falls back to thorough when exhausted)

Premium Features (with LASTSEARCH_API_KEY)

Users with a LastSearch API key (ls_xxx) get enhanced verification:

  • Semantic re-ranking — search results re-scored by semantic query-document relevance
  • Semantic reranking — evidence matched by meaning, not just keywords
  • Multi-provider search — parallel search across multiple sources for broader coverage
  • Multi-pass consistency — claims cross-checked across independent extraction passes
  • Deep reasoning mode — multi-step agentic research with iterative think-search-extract-evaluate cycles, gap analysis, and cross-step claim merging (up to 4 steps, 3x quota cost, 100 deep queries/day)
  • Research Sessions — persistent memory across queries

Free LastSearch key users get a generous daily quota (100 premium queries/day, or ~33 deep queries/day at 3x cost each). When exceeded, queries gracefully fall back to keyword verification (deep falls back to thorough). Quota resets every 24 hours.

Sign up at lastsearch.ai for a free API key — 100 premium queries/day with full verification pipeline.

Quick Start

bash
npx lastsearch setup

This auto-configures Claude Desktop. You'll need a LastSearch API key — get one free at lastsearch.ai/dashboard.

Manual Setup

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

json
{  "mcpServers": {    "lastsearch": {      "command": "npx",      "args": ["-y", "lastsearch"],      "env": {        "LASTSEARCH_API_KEY": "ls_xxx"      }    }  }}

Cursor / Windsurf

Add to your MCP settings:

json
{  "lastsearch": {    "command": "npx",    "args": ["-y", "lastsearch"],    "env": {      "LASTSEARCH_API_KEY": "ls_xxx"    }  }}

HTTP Transport

Run as an HTTP server for browser-based clients, Smithery, or any HTTP-capable agent:

bash
# Start with HTTP transportnpx lastsearch --http
# Or set the port via environment variableMCP_HTTP_PORT=3100 npx lastsearch --http

The server exposes:

  • POST /mcp — MCP Streamable HTTP endpoint
  • GET /health — Health check

Docker

bash
docker build -t lastsearch ./apps/mcpdocker run -p 3100:3100 -e LASTSEARCH_API_KEY=ls_xxx lastsearch

MCP Tools

ToolDescription
searchSearch the web via multi-provider search
openFetch and parse a page into clean text
extractExtract structured knowledge from a page
answerFull pipeline: search + extract + cite. depth: "fast", "thorough", or "deep"
compareCompare raw LLM vs evidence-backed answer
clarityClarity — anti-hallucination answer engine. Three modes: mode: "prompt" (enhanced prompts only), mode: "answer" (LLM answer, default), mode: "verified" (LLM + web fusion)
session_createCreate a research session (persistent memory across queries)
session_askResearch within a session (recalls prior knowledge, stores new claims)
session_recallQuery session knowledge without new web searches
session_shareShare a session publicly (returns share URL)
session_knowledgeExport all claims from a session
session_forkFork a shared session to continue the research
feedbackSubmit accuracy feedback on a result

Note: All tools require a LastSearch API key (ls_xxx). Get a free one at lastsearch.ai/dashboard.

Examples

Quick lookup:

"Use answer to explain what causes aurora borealis"

Higher accuracy:

"Use answer with depth thorough to research quantum computing"

Deep research (multi-step, requires LastSearch key):

"Use answer with depth deep to compare CRISPR approaches for sickle cell disease"

Deep mode runs iterative think-search-extract-evaluate cycles: gap analysis identifies missing info, follow-up queries fill the gaps, and claims/sources are merged across steps with final re-verification. Targets 0.85 confidence across up to 4 steps. Falls back to thorough without a LastSearch key or when quota is exhausted.

Contradiction detection:

"Use answer with depth thorough to check if coffee is good for health, and show me any contradictions"

Research session:

"Create a session called quantum-research, then ask about quantum entanglement, then ask how entanglement is used in computing"

Enterprise search:

"Use answer to search our Elasticsearch at https://es.company.com/kb/_search for our refund policy"

Response structure

json
{  "answer": "Aurora borealis occurs when charged particles from the Sun...",  "confidence": 0.92,  "claims": [    {      "claim": "Aurora borealis is caused by solar wind particles...",      "sources": ["https://en.wikipedia.org/wiki/Aurora"],      "verified": true,      "verificationScore": 0.82,      "consensusLevel": "strong"    }  ],  "sources": [    {      "url": "https://en.wikipedia.org/wiki/Aurora",      "title": "Aurora - Wikipedia",      "domain": "en.wikipedia.org",      "quote": "An aurora is a natural light display...",      "verified": true,      "authority": 0.70    }  ],  "contradictions": [],  "reasoningSteps": []}

Why lastsearch?

FeatureRaw LLMlastsearch
SourcesNoneReal URLs with quotes
CitationsHallucinatedVerified from pages
ConfidenceUnknownEvidence-based score
DepthSingle pass3 modes: fast, thorough, deep reasoning
FreshnessTraining dataReal-time web
ClaimsMixed in textStructured + linked

Reliability

All API calls include automatic retry with exponential backoff on transient failures (429 rate limits, 5xx server errors). Auth errors fail immediately — no wasted retries.

Tech Stack

  • Search: Multi-provider (parallel search across sources)
  • Parsing: @mozilla/readability + linkedom
  • AI: OpenRouter (100+ models)
  • Verification: Hybrid keyword and semantic verification
  • Protocol: Model Context Protocol (MCP)

Agent Skills

Pre-built skills that teach coding agents when to use LastSearch tools:

bash
npx skills add lastsearch-hq/lastsearch-skills

Skills work with Claude Code, Codex CLI, Gemini CLI, Cursor, and more. View skills →

Community

License

Apache 2.0

Data, privacy and terms

This package sends your requests (queries, URLs and documents you ask it to verify) and your LastSearch API key to the hosted LastSearch API at lastsearch.ai. Queries and results are stored there and used, in aggregate and without identifiers, to improve verification, as described in the Privacy Policy. The package itself collects no telemetry. Use of the hosted API is subject to the Terms.

LastSearch is a free, non-commercial passion project run by an individual developer. Answers, citations and confidence scores are AI-generated research, not professional advice; verify anything important against primary sources.

Source: apps/mcp/README.md at commit 7772bd9

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.4.0LatestSep 16, 2026

Score

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  • Reached in the last 30 days25 pts

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  • Auth declared10 pts

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  • Tools listed15 pts

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  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts